ETHIOPIAN CIVIL SERVICE UNIVERSITY

SCHOOL OF GRADUATE STUDIES

FOOD SECURITY AND ITS DETERMINANTES IN RURAL

ETHIOPIA: THE CASE OF KAMBA DISTRICT IN

GAMO GOFA ZONE

BY

MELKAMU MADA DILNESHU

June, 2011

Addis Ababa

Food security and its determinants in the rural

Ethiopia: the case of Kamba district in

Gamo Gofa zone

A Thesis submitted to the Department of Development Economics

Institute of public management and Development Studies

Ethiopian Civil Service University

In Partial Fulfillment of the Requirements for MSc Degree in Development

Economics

By

Melkamu Mada

June, 2011

Addis Ababa

Ethiopia Civil Service University

School of Graduate Studies

As members of the Examining Board of the Final M. Sc. Open Defense, we certify

that we have read and evaluated the thesis prepared by: Melkamu Mada Entitled:

Food security and its determinants in the rural Ethiopia: the case of Kamba district

in Gamo Gofa zone and recommended that it be accepted as fulfilling the thesis

requirement for the degree of: Master of Science in Development Economics.

Approved by Board of Examiners:-

Chairman, Department Graduate Committee Signature

___________________________________ Date _____________

Major Advisor Signature

___________________________________ Date _____________

Internal Examiner Signature

___________________________________ Date _____________

External Examiner Signature

___________________________________ Date _____________

2

DEDICATION

I dedicate this thesis manuscript to both my uncle MELESSE DILNESHU, for he brought up us after the sudden death of our mother, and to

our mother HETEKE DUSSO whom we lost at our infancy

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ABBREVIATIONS AND ACRONYMS

ADLI Agricultural Development Lead Industrialization

AE Adult Equivalent

AIDS Acquired Immunodeficiency Syndrome

DAP Di-ammonium Phosphate

DAs Development Agents

DPPA Disaster Prevention and Preparedness Agency

ECA Ethiopian Central statistics Authority

EGS Employment Generation Scheme

EHNRI Ethiopia Health and Nutrition Research Institute

FAO Food and Agricultural Organization

FEWS Food and Early Warning System

FGT Foster, Greere and Thorbecke

FSCO Food Security Coordination Organization

FTCs Farmers Training Centers

GDP Gross Domestic Product

HFS Household Food Security

HH Household

HIV Human Immunodeficiency Virus

ICRA International Crop Research Agency

IFAD International Fund for Agricultural Development

IFPRI International Food Policy Research Institute

ILRI International Livestock Research Institute

Kcal Kilocalorie

Kg Kilogram

Km Kilo meter

LDCs less Developed Countries

m.a.s.l Meter above sea level

ML Maximum Likelihood

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MoARD Ministry of Agriculture and Rural Development

MoFED Ministry of Finance and Economic Development

NGOs Non Governmental Organizations

PAs Peasant Associations

PASDEP A Plan for Accelerated and Sustain Development to End Poverty

PSNP Productive Safety Net Programme

RBS Regional base line survey

RDFS Rural Development and Food Security

RR10 Rural Rode

SD Standard Deviation

SNNPR South Nations Nationalities Peoples Region

UN United Nations

UNDP United Nations Development Programme

VIF Variance Inflation Factor

WB World Bank

WFP World Food Programme

WoA Woreda Agricultural Office

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BIOGRAPHY

Melkamu Mada was born in Dorze, Chencha woreda, Gamo Gofa zone of South Nations

Nationalities Peoples Region on November, 1976. He attended his junior and secondary

education (9-12) at Chencha High School. He joined the then Jimma College of Agriculture in

1999 and graduated in diploma in Agriculture (Horticulture) on July 2000. After graduation, he

was employed by the Ministry of Agriculture in the Kamba woreda and served for about two

years. Then, he joined the then Alemaya University of Agriculture (AUA) in 2003 and graduated

with B.Sc. Degree in Agriculture (Agricultural Economics) on July 2007. The author served as

disaster prevention and preparedness expert and woreda agriculture Office Head from October

2000 to until he joined the school of graduate studies at Ethiopian Civil Service University on

September 2009/2010 to specialize in Development Economics.

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ACKNOWLEDGEMENT

I would like to express my deep gratitude to my research advisor Tadesse Kuma (Ph.D.) for his

professional suggestions, thought guidance and over-all assistance from the beginning of the research

proposal up to the end of thesis write up. Thus, I am very much indebted to him for all his support

and willingness to advise me on my day-to-day efforts, and this has enabled me to finalize the study.

I wish to greatly acknowledge the financial support provided by Ethiopian Civil Service University

for sponsoring and covering the costs associated with data collection for the thesis work.

My special thanks also go to the Kamba woreda administration and agriculture office without whose

permission to join the M.Sc. program and without whose support this research document would have

not been able to be materialized. My appreciation and thanks are also extended to Mr. Monaye

Mosole, Mr. Asrat Agoze, Mr. Debebe Mulgeta, Mr. Alene Abeje and Dr. Tsgalem H/Mikael for

their positive and immediate response and provision of computer facility. My genuine appreciation

goes to all Kamba woreda agriculture office employees for their unreserved and unforgettable

assistance and encouragements during my study and data collection campaigns.

I would like to extend my special thanks to Kamba woreda development agents Abraham Gamo,

Asire Ayele, Andargachew Jemaneh, Mesafint H/Michael, Reta Wolde, Said Khalifa, Takele

Mukulo, Tirunesh Lema, Wogaso Gassa, Zena Ali, Zena Dea who devoted their precious time for the

data collection of this thesis. I am also very much grateful to 200 rural farmers for their

participation and for devotion of their precious time in answering the research interview questions.

No words can suffice to express my feelings of gratitude to my brother Ato Mitiku Mada(LLM) and

his wife weizero Senait Tadesse and Akililu Mada for their financial and moral support which they

offeried to me throughout the duration of study years.

Finally, my deepest gratitude goes to my wife Marta Beyene who had shown tremendous patience,

made sacrifices, and shouldered the social, economic and family affairs including nursing of my sons

during the time of my graduate program study.

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TABLE OF CONTENTS Page ABBREVIATIONS AND ACRONYMS……………………………………………………………….....I BIOGRAPHY………………………………………………………………… ........................................ III

ACKNOWLEDGEMENT …………………………………………………… ........................................ IV

TABLE OF CONTENT…………………………………………………………………………………...V

LIST OF TABLES………………………………………………………………………………………VIII

ABSTRACT………………………………………………………………….. ........................................ IX

1 CHAPTER ONE ………………………………………………………………………………………....1

INTRODUCTION……………………………………………………………………………………...…..1

1.1 Background ................................................................................................................................... 1

1.2 Statement of the Problem ............................................................................................................... 4

1.3 Objectives of the Study .................................................................................................................. 6

1.4 Significance of the Study ............................................................................................................... 6

1.5 Limitations of the Study ................................................................................................................. 7

1.6 Organizations of the Study ............................................................................................................. 8

2. CHAPTER TWO ………………………………………………………………………………………..9

REVIEW OF LITERATURE………………………………………………………………………………9

2.1 Definitions and Overview of Food Security .................................................................................. 9

2.1.1 Food security defined .............................................................................................................. 9

2.1.1.1 Sufficiency ........................................................................................................................... 9

2.1.1.2 Access ................................................................................................................................ 10

2.1.1.3 Security .............................................................................................................................. 10

2.1.1.4 Time .................................................................................................................................. 10

2.1.1.5 Vulnerable ......................................................................................................................... 10

2.1.2 Household food security: An economic perspective ................................................................... 11

2.1.3 Determinants of Household food Insecurity ............................................................................... 12

2.2. Measures taken to overcome the food security problem ............................................................... 17

2.2.1 Agricultural Extension Services............................................................................................. 18

2.2.2 Agricultural Research ............................................................................................................ 18

2.2.3 Food Security Programme ..................................................................................................... 19

2.2.4 Productive Safety Net Programme ......................................................................................... 20

2.2.5 Voluntary Resettlement Programme ...................................................................................... 20

2.2.6 Water harvesting ................................................................................................................... 21

2.2.7 Expansion of Small-scale irrigation ....................................................................................... 21

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2. 3 Main challenges that affect the success of food security .............................................................. 22

2. 3.1 Climate change .................................................................................................................... 22

2.3.2 Technology adoption problem ............................................................................................... 22

2. 3.3 Rapid and unhindered population growth.............................................................................. 23

2.3. 4 Poor Input and output market system .................................................................................... 23

2.4 Empirical Literature ..................................................................................................................... 24

2.5 Methodologies of measuring food security: .................................................................................. 27

2.5.1 Household Caloric Acquisition .............................................................................................. 28

2.5.2 Method for generating data .................................................................................................... 28

2.5. 3 Advantages of this method ................................................................................................... 28

2.6 Expected Contributions of the study ............................................................................................. 29

2.7 Comments on the Reviewed Literatures………………………………………………………….....29

CHAPTER THREE ……………………………………………………………………….……………....30

RESEARCH METHODOLGY…………………………………………………………………………....30 3.1 Description of the study area …………………………………………………………………………30

3.1.2 Livelihood Strategies in the study area .................................................................................. 30

3.1.3 Population ............................................................................................................................. 31

3.1.4 Religion ................................................................................................................................ 32

3.1.5 Agriculture ............................................................................................................................ 32

3.1.6 Crop Production ................................................................................................................... 33

3.1.7 Livestock and Poultry Production .......................................................................................... 33

3.1.8 Agricultural Extension .......................................................................................................... 34

3.1.9 Input Supply ......................................................................................................................... 34

3.1.10 Rural road ........................................................................................................................... 34

3.1.11 Market……………………………………………………………………………………......35 3.12 Unexploited opportunities that exist in the woreda…………………….……….……………...35 3.2 Methods and Sources of data collection…………………………………………………….………...35

3.2.1 Methods of data collection………………………………………………………………………35 3.2.2 Method of data analysis…............................................................................................................37 3.3 Theoretical model ............................................................................................................................ 38

3.4 Empirical model .............................................................................................................................. 42

3.5 Variables and working hypothesis…………………………………………………………………….43

3.6 The dependent variable of the model….................................................................................................44

3.7 Independent variables………………………………………………………………………………....44

3.8 Interpretation of the coefficients of the logistic regression model……………………………………49

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3.9 Marginal effects result in logistic model ........................................................................................... 50

3.10 Testing Multicollinearity………………………………………………………………………...50

3.11 Measuring intensity of Food security …………………………………………………………....51 4. CHAPTER FOUR ……………………………………………………………………………………...52

RESULTS AND DISCUSSION…………………………………………………………………………..52

4.1 Measuring food security status of households .............................................................................. 52

4.2 Demographic and socio-economic characteristics ......................................................................... 53

4.3 Incidence of food security by households’ factors………………………………………………….66

4.4 Extent of Food security………………………………….................................................................68 4.5 Summary of mean difference and household scores……………………………………………… 68

4.6 Analysis of determinants of food security……………………………………………………….. 70

4.7 Discussion on the Significant Explanatory Variables .................................................................... 73

4.8 Major Agricultural Problems ........................................................................................................ 78

4.9 Extension services ...................................................................................................................... 79

4.10 Coping Strategies ....................................................................................................................... 80

CHAPTER FIVE ...................................................................................................................................... 84

SUMMARY AND RECOMMENDATION………………………………………………………………83

5.1 Summary of findings ................................................................................................................. 83

5.2 Recommendations........................................................................................................................ 87

Reference………………………………………………………………………………………….....……91

Appendices ………………………………………………………………………………………………. 96

Appendix 1:- Conversion Factors to Estimate Tropical Livestock Unit equivalents …….................96 Appendix 2: Conversion Factors Used to Compute Adult-Equivalent (AE)…………………… ….96

Appendix 3: calorie value of food items consumed by sample households………………………...97

Appendix 4: Summary of the Survey Questionnaire……………………………… ……………….98

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LIST OF TABLES Page Table 1 - population growth rate of Kamba woreda………………………………………….. ......... 31

Table 2-Religion distribution of the study area………………………………………………….. ..... 31

Table 3- Types, codes and definition of variables in the logit model……………………………….49

Table 4- Food security status of sample households………………………………………… .......... 53

Table 5-Distribution of sample households by family size in number……………………….. ......... 54

Table 6- Household food security by sex of household head………………………………. ............ 55

Table 7- Household food security by educational status of household head………………. ............. 56

Table 8- Distribution of sample households by number of months food item purcased…………….57

Table 9- Distribution of sample household heads by age……………………………………. .......... 58

Table 10 - Distribution of sample households by farm size per household(in hectare)……………..59

Table 11- Distribution of sample households by Livestock Holding by TLU…………….. ............. 60

Table 12- Distribution of sample households by oxen……………………………………… ........... 61

Table 13- Distribution of households by amount of food aid received in Kg…………… ................ 62

Table 14- Distribution of sample household by status of use of technology………………………...63

Table 15- Distribution of sample households by off-farm income in birr…………………………...64

Table 16- Distribution of sample households by irrigation farm size in hectare……………………65

Table 17- Distribution of sample households by infrastructure distance in Km ............................. 66

Table 18:- Incidence of food security by sample households’……………………………………….67

Table 19- Summary Statistics of continuous variables included in the descriptive statistics……….69

Table 20: Summary statistics of discrete variables included in the descriptive statistics .................. 70

Table- 21 VIF value of continuous variables……………………………… .................................... 71

Table 22- Contingency coefficient for discreet variables………………………………………...….71

Table 23- The maximum likelihood estimates of the logit model………………………….. ............ 72

Table 24-Major agricultural problems encountered in the study area ……………….. ..................... 79

Table 25:- Coping strategies common in Kamba woreda…………………………………… ........... 81

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ABSTRACT

A better understanding of the factors that affect the status of food security at household level is

required for the organization of technical research for formulation of the development of policies

and for shaping the direction of action for food self-sufficiency. Consequently, this study is

expected to generate ideas that would be useful to reveal the seriousness of the problem and

identify the determinants of household food security and coping strategies and recommendations.

In order to achieve these objectives biophysical, demographic and socio-economic data were

collected from 200 randomly selected households in Kamba woreda of Gamo Gofa Zone in South

Nations Nationalities Peoples Region. A two stage sampling procedure was used to select 13

PAs, and 200 sample respondents from a total of 38 PAs in the woreda. A survey was conducted

to collect the primary data from sample respondents. Supplementary, secondary data were

collected from various sources. The data was analyzed using descriptive statistics like mean,

standard deviation, percentage and frequency distribution. Univariate analysis such as T-test

and Chi-square (χ2) tests were also used to describe characteristics of food secure and food

insecure groups. The survey results show that only 39.5% of sample farmers were food secure. A

logistic regression model was fitted to analyze the potential variables that affect households'

food security status in the study area. Among 13 explanatory variables included in the logistic

model, 10 of them were significant at less than 5% level of significance. These were, family size,

farm size, number of livestock owned, total annual off-farm income, educational level of

household, technological adoption of household head, household head participation in public

meeting, household head extension contact trend, number of months food purchased and quality

of land .The estimated model correctly predicted 96.5% of the sample cases, 96.1% food secure

and 96.7% food insecure. Thus, identifying, analyzing and understanding those factors that are

responsible for household food security status and its determinants is important to combat the

problem of food security at the household level. The study findings suggest that in selecting

priority intervention areas, the food security strategy should consider statistically significant

variables as the most important areas.

1

CHAPTER ONE

INTRODUCTION

1.1 Background

Ethiopia, as one of the low income countries of the world, is facing repeated macro-and micro

level food insecurity coupled with environmental degradation and depletion. In the last three

decades, it has not been possible to produce adequate food to meet the needs of the fast growing

population, attributed mainly to fragmented land holdings, successive droughts, untimely and

unpredictable rainfall, antiquated farm technology, lack of farm input, low producer prices and

other ecological factors. Earlier studies have estimated Ethiopia’s food insecure people to be

around 40-50 percent of total population and at least 50% of farm house production does not

satisfy basic needs and most of them face a hunger season every year (Yohannes, 2002;

Devereux, 2001).

The proportion of people who are unable to attain their minimum nutritional requirement is

reported to be thirty three (33%) for rural and thirty (30%) for urban population (IFPRI, 2009).

In Ethiopia, food insecurity is seen as the most important feature of development challenges.

Every year, more than 4 million people, particularly in the rural areas have problems of getting

enough food for themselves (Tassew, 2004). Currently, 5.23 million people will continue to

require emergency food assistance up to December 2010 according to the Joint Government and

Humanitarian Partners’ February 2010. Report of FAO/WFP in 2004, 2007 and 2011 shows the

existence of bumper harvests at the national level. But achieving food security at national or

regional level does not necessarily guarantee food security at district or households’ level. There

exists disparity among districts and households’ in production function and motives for

productivity. Even if a households’ is food secure it does not ensure that each member of the

households’ is food secure due to discrimination in food distribution within households'. The

geographical, environmental and medical factors that affect food security are important for their

respective fields but social factors are significant for policy making and use by development

practitioners.

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Food insecurity in SNNPR remains a multifaceted and complex problem in which lack of access,

as well as availability and quality of food still play an essential role. Several factors should be

taken into consideration including extreme poverty, poor access to infrastructure, lack of

productive assets, weaknesses in the marketing system and transport bottlenecks and others.

According to a recent estimate, about 59 percent of the households’ in the region are labeled as

food insecure (RDFS 2009).Regional average per capita calorie availability is about 1800 which

is less than the international minimum standard of 2100 calories and much less than the standard

for an adequate diet of 2400calories (SNNPR Regional base line survey,2007). Despite the

overall improvement in alleviate food security, most poor and very poor households’ in these

areas (20 to 35 percent of the total population) face chronic food shortages due to very high

population density, shortage of land, and declining soil fertility. According to the regional

baselines, even in a normal year, the poor and very poor in most of these regions rely on food aid

(emergency or PSNP programs) to meet 5‐25 percent of their basic food requirements (FEWS

NET 2010). In the region, population growth is as high as 3.6% in some years, far above the

national average of 2.9%, implying population may have exceeded the carrying capacity of the

already fragile environment production capacity (SNNPR Regional base line survey, 2009). This

shows that in the region food supply and demand are not moving in equal pace.

Kamba woreda, where this research was done is one of fifteen woredas of Gamo Gofa zone. It

has 38 peasant associations (PAs) with total population of 155,748. Out of this, 5,612(3%) live in

urban and 150,132 (97%) live in rural (CSA, 2007). It has three agro-ecologies: highlands

(dega), midlands (woinadega) and lowlands (kola). It is about 635kms away from Addis Ababa

and 105km from Arbaminch, zonal town.

Kamba woreda is one of the major food deficit and famine-prone woreda in Gamo Gofa zone:

SNNPR. Food insecurity, poverty and vulnerability to livelihood crises have increased in the

woreda since the drought years of the middle 1980s and early 1990s (WFP 2003). Despite the

overall improvement in the level of food security in the region and in the country, most poor and

very poor households’ in Kamba face chronic food shortages due to very high population

density, shortage of land, poor access to infrastructure and declining soil fertility. According to

3

the livelihoods baselines survey (1994/95), even in a normal year, the poor and very poor in

Kamba woreda rely on food aid (emergency or PSNP programs) to meet 5‐25 percent of their

households’ food requirements. A review of food aid recipients in the different kebeles of the

woreda shows that the number of households’ that depend on seasonal food assistance has

increased from year to year. According to Kamba woreda agricultural office early warning report

(2003-2009) the number of food aid recipient increased from year to year, 14,200 beneficiaries in

2003 and 22,062 beneficiaries in 2009. Food security problem in Kamba derived directly from

dependence on undiversified livelihoods based on low-input, low-output, full dependence on rain

fed agriculture, decreasing land holding size and increasing population, week agricultural

extension services, recurrent drought and natural resource degradation (land, water, forest, and

rangeland), persistent livestock disease and lack of market access, lack of alternative off-farm

employment and others in the study area have made the food security situation worse. Kamba

woreda is not among those areas that are showing agricultural growth and technological change

in the region. Rather, Kamba agrarian conditions represent continuity more than change, as

demonstrated by its inability to meet the food demand of the woreda’s rapidly growing

population.

The dominant factors that contribute for the chronic food insecurity problem in the Kamba

woreda are poor crop and pasture production, infrastructure problem mainly road, abnormal food

price and livestock disease. The poor performance of the agricultural sector in the area directly

creates supply problems and indirectly creates demand problems by contradicting the producer’s

access to sufficient income. The agricultural productivity in the area strongly depends on rain

fed, which mostly behaves an irregular start and end (poor distribution). In that area, below

normal rain is common and leads to poor harvest, poor pasture and poor food availability.

Kamba woreda is known with its road problem. Before fifteen years, the woreda faced serious

drought and due to road problem life saving rations were dropped from air. Even nowadays no

food crops are transported in to the woreda and out of the woreda. Households’ in the area face

unusual prices during normal time and farmers cannot get fair price for their products during

good harvest seasons.

4

Food self-sufficiency has remained the declared goal for federal, regional and woreda

government of Ethiopia. Similarly, the problem of food security has continued to persist in the

rural areas like Kamba. The Kamba woreda administration and different NGOs implement food

security programs like productive safety net, voluntary resettlement, provision of improved

technologies for the farmers, water harvesting programs have been implemented in the area. But

the progress is not significant, so assessment of food security challenges at woreda and

households’ level to identify the major determinants is fundamental. Having this background,

this study tries to investigate the food security and it’s determinates in rural households’ in

Kamba woreda, Gamo Gofa zone: SNNPR.

1.2 Statement of the Problem

Over the past ten decades, Ethiopia has been challenged by food insecurity problem. In Ethiopia,

the trend in growth of domestic food production matched population growth only in the 1960s

(Markos, 1997). In spite of the fact that Ethiopia has abundant natural resources, most of its

socioeconomic indicators are extremely low and discouraging. Numerous studies have confirmed

that there is a problem of food security in Ethiopia with wide range of area to be covered and

large number of people to be attended for different identified causes of food security problem.

Among these causal factors, per capita land holding with increasing population growth, livestock

availability, education, per capita income of the households’ from agricultural and non

agriculture activities, soil fertility, conflict, under-funded agriculture are the major and

commonly mentioned factors (Gebre-Selassie, 2005, Negatu, 2004,Ramakirshina et al, 2002,

Madeley 2000).

Ethiopian government and international donors have been implementing different categories of

responses to attain food self–sufficiency and to reduce food aid dependency. These categories are

based on supply based responses (increasing the level and stability of production, increasing food

reserve, and influencing international food markets), demand based responses (improving

income, productive assets available to vulnerable groups, and other market and non-market

transfer), and disaster prevention and preparedness capabilities having adequate early warning

systems (IFPRI, 2003). Despite such efforts, food insecurity remains the main challenging

5

problem in our country and the need for food aid has been increasing. This shows that there is

mismatch between food demand and supply.

In the last two decades, Kamba woreda have been identified as chronically food insecure area

and that cannot adequately feed its rapidly growing population .In the woreda, farmers do not

produce enough food even in good harvest seasons to meet their own consumption requirements.

Therefore, they have continued to depend on relief assistance to fill the food deficit. As a

result of this annual food deficit people migrate from highlands every year in search of jobs

outside the district and within the district. High dependence on relief assistance and the existence

of migration shown there is high annual variability in food production and availability, which

confirms the existence of food security problem among the households’ of the district. Making

their living on marginal, moisture stressed, heavily degraded and less productive land,

households’ in the Kamba woreda have been facing persistent food shortages. On top of the ever

decreasing size of land holding due to increasing population, continuously decreasing per-capita

production, high dependence on rain fed agriculture, recurrent drought and natural resource

(land, water, forest, and rangeland)degradation, lack of infra-structures, lack of access to market,

persistent animal diseases, week extension system(absence of credit service, lack of improved

technologies, absence of crop diversification), low family income, lack of alternative off-farm

employment, practicing bad cultural habits and others in the study area have made the food

security situation worse. Realizing this issue, many governmental and non-governmental

organizations are intervening at least to decrease the adverse effects of the food security

problem. But, there is yet little success. Aware of these facts, this study was designed to identify

the factors that contribute to households’ food insecurity problem and to the severity of the

problem in the rural areas of Kamba woreda, and through that make recommendations to

improve the effectiveness of interventions. Having this background in mind the study has put

forward the following research questions.

6

Research questions:

• What is food security? What efforts have been made by the international and national

governments to eradicate the problem? What are the success stories and the challenges

that have been faced?

• What are the determinant factors that affect food security problem in the rural

households’ in the Kamba woreda?

• What coping strategies do food insecure households’ uses to make their livelihood during

time of sever food shortage?

• What is the contribution of governmental and non- governmental programs to address the

problem?

To address the above research questions, the study has applied logistic regression method of

analysis by using data generated from 200 households’.

1.3 Objectives of the Study

The main objective of this study is to analyze the food security status of the rural households’

and its determinants in the Kamba woreda of Gamo Gofa zone: SNNPR. The specific objectives

of this study include:

1. To investigate how households’ level socio-demographic structure affect food security.

2. To identify the major factors that contribute for some households’ attain food security

while others not.

3. To record coping mechanisms of households’ during adverse covariant shocks.

4. To investigate how households’ food security status is related to households’ food intake

and dietary diversity.

5. To identify policy measure those improve the households’ status of food security problem

in the area.

1.4 Significance of the Study

Population growth coupled with environmental degradation, drought, a largely stagnant

agricultural technology, poor institutional arrangements, inefficient output and input markets,

inadequate infrastructure and external factors have all contributed to the aggravation of food

security problem in the study area. The woreda administration of the woreda study area has been

7

trying to increase food security at both households’ and woreda levels through these small-scale

farmers. Despite all these efforts, majority of households’ in the area have been facing series

food security challenges. Identifying determinates of households’ food security problems have

been studied by many researchers in the country. This study has focused on assessing

determinates of households’ food security problem in Kamba woreda in which no similar

research has been done to the best of own knowledge. The various factors that affect

households’ food security status were discussed so that recommendations can be made for the

adoption of better strategies and actions to assist small-scale producer farmers to address

households’ food security problem in the woreda. This study helps to identify gaps in small-

scale farmers and come up with reasons why small- scale farmers are food insecure.

The result of the study provides policy related information that helps to prioritize among the

many possibilities depending on the relative extent of influences of its determinants. More

specifically, it helps concerned bodies in their effort to formulate policies and develop

intervention mechanisms that are tailored to the specific need of the study area. Furthermore, this

study attempts to make further contribution to the previous studies and can be used as a source

material for further studies.

1.5 Limitations and scope of the study

The study specifically has focused on identifying major determinants of food security problem at

households’ level by comparing direct calorie consumption per adult equivalent with the

minimum requirement by classifying sample households’ as food secure and insecure and then

looking at the extent of food security problem in Kamba woreda. The study covers only 13 of the

38 PAs of the study area. Moreover, the study deals with a limited number of households’ and

focused on the dimensions and determinants of food security problems. Besides to this, the data

were collected at one time period and during the time of food shortage faced by the households’

in the study area. The scope of this study was limited by time, budget and other resource

limitation. Even if the study was restricted in terms of its coverage its outputs can be used as a

spring board for more detailed and area specific studies.

8

1.6 Organization of the study

The rest of this thesis is organized in six chapters. Chapter two deals with review of literature

that includes theoretical frameworks of food security and empirical studies made in the country

and elsewhere in the world. Chapter three presents a brief description of the study area while

chapter four deals with methodology of the research. Results obtained are discussed in detail in

chapter five. Chapter six presents summary and conclusions of the study.

9

CHAPTER TWO

REVIEW OF LITERATURE

2. 1 Definitions and Overview of Food Security

This section reviews the literature on food security. This will be done in four sub-sections.

Section one provides brief definitions of what food security is and determinants of households’

food security are discussed in this section. In section two much of the discussion will revolve

around what efforts have been made at global, regional and at country level to close down the

food security problem and what are success and failures of the past efforts. In section three a

brief discussion of empirical research that has been carried out on food security in the country

and outside the country, and in the last section how food security has been measured and

expected contribution of this study for the literature world is discussed.

2.1.1 Food security defined

Food security is defined in different ways by international organizations and researchers.

According to Smith et al. (quoted in Maxwell, 1996), there are close to 200 definitions of food

Security but the one most commonly used and this study concentrates is the one given by the

Food and Agricultural Organization (FAO) which states that, “Food security exists when all

people, at all times, have physical and economic access to sufficient, safe and nutritious food to

meet their dietary needs and food preferences for an active and healthy life” (FAO 1996, Rome

Declaration 1996, page 8). Food security may be generally understood as, "Secure Access to

Sufficient Food at All Times.” This definition integrates access to food, availability of food, and

the biological utilization of food as well as the stability of all these. These details are provided

below:

2.1.1.1 Sufficiency: Sufficiency is commonly understood and measured by the number of

calories an individual requires to live an active and healthy life (S. Maxwell & M. Smith,

1992).Although daily caloric requirements for men, women and children have been estimated by

nutritionists, the broad applicability of these caloric intake standards has been questioned(K.

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Bagachi et al,2002).An individual's perception of his/her own hunger and the amount of food

required to live an “active and healthy” life have been found to vary greatly(J. Coates, et al,

2002).Despite these debates, food sufficiency is generally understood as the amount of food

required by an individual to meet dietary energy requirements as defined by the Food and

Agricultural Organization(R. Gardiner, 2002).

2.1.1.2 Access: Access to the means of acquiring food, whether through production, purchase

or exchange, is central to contemporary definitions of food security. The key determinants of

food access are physical, economic, political and socio-cultural. Human and physical capital,

households’ assets, property resources, markets, and a variety of social contracts at the

households’, community and state levels, directly affect an individual’s level of access (S.

Maxwell & M. Smith, 1992).Access to the means of food acquisition is highly dependent on

gender biases and social forces.

2.1.1.3 Security: Security refers to the extent to which the access to the means of acquiring

food is vulnerable. Vulnerability is a function of risk and insurance. Asset ownership, human and

social capital, government safety nets, and the activities of non-governmental organizations

(NGO's) all contribute to an individual or household level of insurance, while variability in crop

production, changes in food prices and food supply, employment, and wages all influence the

risk profile (S. Maxwell & M. Smith, 1992).

2.1.1.4 Time: Food insecurity may be chronic, cyclic or transitory based on factors such as

seasonal patterns and income regularity. Households’ or individuals that are continually unable,

or are at risk of being unable, to meet caloric needs are categorized as chronically food insecure.

Households’ experiencing a temporary decline in the ability to meet caloric needs is categorized

as having transitory food insecurity. Households’ experiencing re-occurring, regularly timed

periods of food insecurity (e.g. hunger seasons) are understood to be facing cyclic food

insecurity (S. Maxwell & M. Smith, 1992).

2.1.1.5 Vulnerable: Vulnerability is strongly related to the concept of food insecurity,

highlighting the element of risk that households’ face in their production, income, and

11

consumption activities. Vulnerability can be defined as the likelihood that a specific population

group will experience an acute decline in their food access. In addition to the risks that

households’ face, vulnerability further implies that these groups are unable to sufficiently cope

with those threats to effectively protect their basic food access. Female-headed households’, the

aged, the disabled, and other disadvantaged groups with low levels of households’ labor and

insufficient means of support from family members and the community are also typically

included as being among the most food insecure and vulnerable as well. Other households’ are

vulnerable because they live in areas susceptible to natural or man-made disasters. households’

under the extreme threat of conflict, drought, and other risks, particularly those households’

lacking a diversified income and asset base to cope with those risks, are also considered among

the most food insecure and vulnerable groups.

2.1.2 Households’ food security: An economic perspective

Economic approaches to food security have traditionally focused on assessing aggregate levels of

food supply, agricultural production, and the balance of agricultural trade (World Bank1986). In

the 1970s, food security was defined at the macro level as the ability to avoid short-term deficits

in aggregate food supply (Staatz JM Econ 1990) and it was directly linked to grain stocks at the

global and national level (Holmboe-Ottesen G1990). During the 1980’s, this macro-level

understanding was replaced by a focus on individual-level and households-level concepts of food

security, emphasizing access, vulnerability and entitlements (S. Maxwell & M. Smith.1992).

This shift was largely influenced by the pioneering work of economist Amartya Sen.

From an economic perspective, malnutrition was increasingly recognized as the individual-level

manifestation of a complex combination of households’, community, regional, national, and international

factors (Marek T, 1992). Seminal work on the phenomenon of famine by Sen (an essay on entitlement

and deprivation,1981) brought attention to the issue of access to food by households’ and by individuals,

which could be constrained by economic, social, and cultural factors and was most often a chronic, not

transitory, condition at the households’ level. Food insecurity could occur at the households’ level, and

was occurring, in the absence of regional and national food insecurity.

The neoclassical economic theory of households’ production added further to the concept of food

security by emphasizing the decision-making processes within the households’ that determine

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how scarce resources are allocated. Since households’ have limited access to resources and

struggle to fulfill a variety of basic needs, procurement of food competes with acquisition of

health services and other goods and services. Therefore, food needs are necessarily the most

dominant basic needs for a given households’ subsistence or survival (Maxwell S, Frankenberger

TR 1992).

Macro-level food security focused on food availability (supply), most of the recent households’

food security frameworks are concerned primarily with households’ access to food, although all

recognize that access is just one component of households’ food security as discussed above. At

the households’ level, food security is determined by a household’ current food supplies, past

stable food supply, and potential future supply.

2.1.3 Determinants of households’ food insecurity

To obtain their food, households’ typically either: (a) grow it and consume from their own

stocks; (b) purchase it in the marketplace; (c) receive it as a transfer from relatives, members of

the community, the government, or foreign donors; or (d) gather it in the wild. The factors that

limit the ability of households’ to grow, store, purchase, gather or receive transfers of food will

vary by location, across socio-economic groups, and over time. Once the basic sources of food

have been identified, it is necessary to investigate the often complex interaction of agro-physical

and socio-economic processes that limit a households’ ability to obtain sufficient quantities of

food from each source.

Food security is generally affected by two major determinants: Availability of food and

accessibility to it (Andersen, 1997). The Same source also showed that human resource

development, non-food factors, including education, health care, and clean water, population

growth, urbanization and displacement of people greatly influence food insecurity and human

nutrition. This source further stipulated that natural resource and agricultural inputs are critical

determinants of food security. Food insecurity is due to a variety of reasons, and the FAO/UNDP

(1987) cited in Getachew (1995) suggested, i) the relatively high density of human and livestock

populations and the resulting squeeze of land resources; ii) the inability of agricultural practices

to sustain the required productivity levels of land; iii) insufficient level of adoption of modern

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farm technology; iv) extensive and often irreversible levels of land degradation; v) the value

placed on livestock, specially cattle, in the social economic system and the accomplishing desire

to maintain large livestock holdings.

According to Hoddinott (2001) households’ food security (HFS) issues cannot be seen in

isolation from broader factors. He viewed these factors as physical, policy and social

environment. And he argued that the physical factor play a large role in determining the type of

activities that can be undertaken by rural households’. Government policies on the other hand

toward the agricultural sector will have a strong effect on the design and implementation of

households’ food security interventions. Likewise the presence of social conflict, expressed in

terms of mistrust of other social groups or even outright violence, is also an important factor in

the design and implementation of interventions. Hoddinott (2001) expressed that resources or

endowments that food security of households’ can be divided into two broad categories: labor

and capital. Labor refers to the availability of labor for production. It incorporates both physical

dimension-how many people are available to work as well as“knowledge” and human capital

dimensions. On the other hand, capital refers to those resources such as land, tools for

agricultural and non agricultural production, livestock, and financial resources; that when

combined with labor produce income. In turn the house- holds allocate these endowments across

different activities such as food production, cash crop production and non-agricultural income-

generating activities in response to the returns each activity generates. In addition, households’

may receive transfer income from different sources, which determines households’ income.

Hoddinott (2001) further described that households’ face a set of prices that determine the level

of consumption that can be supported by the given level of income. Accordingly, consumption is

divided between those goods that affect households’ in individual food security and all other

goods. Goods that affect food security include food consumption at the households’ level

(referred to as food access in much of food security literature), goods directly related to health

care; and goods that affect the health environment. These three goods affect illness & individual

food intake, which in turn generates nutritional status or food utilization. Finally Hoddinott

14

(2001) noted that food security is not static over time. There are second rounds, or feedback

effects.

Lathan (1997) has clearly indicated that income received from cash crops or wage earnings and

prices paid for purchased items influence a rural population’s food security. Further, the author

stated that inadequate land holdings; landlessness and sharecropping are all powerful causes of

family insecurity. Lathan has also identified that a ‘shock’ often precipitates households’ food

insecurity. The shock can adversely influence food production (suddenly threatening farm food

availability). There are many different kinds of shocks, like serious illness, which may result in

reduced agricultural production in a farm family; loss of rural job; farm production crises, such

as failure of the rains, or a plague of locusts or some other agricultural catastrophe. Any crisis

that has an adverse impact on the livelihood of the family may also result in households’ food

insecurity.

In the Horn of Africa, for example, a leading determinant of food insecurity is low levels of per

capita food production. The primary constraints to improved food production in the region are a

combination of low and erratic rainfall, high population densities, deforestation and, as a result,

an accelerated deterioration in soil quality and crop yields. Poor market infrastructure and an

unfavorable policy environment which leads to high and variable prices for inputs and low

producer prices further undermine productivity in many countries in the region (Frank Riely,

Nancy Mock1999).

A case study of resource and food security of Wobera District of East Hararghe Zone

(Getachew, 1991) showed that sufficient conditions exist for chronic and transitory food

insecurity among the households'. These conditions are: first, land, one of the most important

resources for food production, is scarce among the study households’. Second, other households’

resources such as livestock have fallen dramatically. Third, due to climatic hardship, even cereal

major producing areas remain deficit, leaving both cereal and cash crop dependent households’

in a disadvantaged food supply position. Fourth, the administrative apparatus of Ethiopia (both

15

past and present) neglected the rural sector with no or realistic development strategies to reduce

risks of food insecurity.

The same source further showed that agro-ecological induced variation of holding size and plot

distribution and ox-ownership, as an important factor in determining households’ resource

endowment and the ability to perform agricultural activities, came out to be factors which

determine the food security situation among the sample households’. Moreover, other factors that

were given due attention in the study were labor, land-to-man ratio, ability of the area to offer

cash crop and off-farm income, grazing land, households’ indebtedness, cash block (off farm

employment income, cash crop income, livestock income and borrowing), market price,

households’ expenditure (obligation to the state, rural institution, the households’ itself and

other households’).

In a case study of Social and Demographic Characteristics Habro woreda, using logistic

regression model, Getachew (1993) showed that there is a statistically significant relationship

between resources held by a households’ and its level of food security. It was confirmed that

those households which hold land less than three Timad, do not own any oxen, have a small

households’ adult equivalent size and earn non-farm income of less than Birr 500 (or nothing at

all) are those most at risk of food insecurity among the sample population. Consequently, the

researcher showed that the levels of income and farm size are the most important resources

determining food security when other factors such as favorable climatic conditions and low pest

outbreak are satisfied. In other words, a larger land size and high income increase the chances of

maintaining food security. Poor target groups often lack access to institutions and services which

could help them in improving their subsistence production and income (SLE, 1999; cited in

Ayalneh 2002).

Moreover, it is a combination of availability, access and the chance of receiving external

assistance that determines the households’ food security. As explained in FAO (1991) the

problem of households’ food security is not simply one of agricultural output, but encompasses

all factors affecting a households’ access to an adequate year round supply of food. Thus, the

16

problem of households’ food security is not simply one of next season’s crops, but can also

include factors as diverse as deforestation, seasonal variations in food supply, availability of

fodder and other forest foods, shifts from subsistence to the cash economy, and even the timing

of cash needs as school fees.

Ayalneh (2002) in his study of Land Degradation, Impoverishment and Livelihood Strategies of

Rural households in Ethiopia, showed that factors that have contributed to transitory and chronic

food insecurity in rural Ethiopia are various and varied, ranging from political and socio-

economic to environmental. Among the political factors he listed inappropriate agricultural and

marketing policies, and political conflict both at national and local level. Among the socio-

economic factors are demographic characteristics of rural households’ inadequate resource

endowments, inadequately developed infrastructure such as school, hospital and roads, etc. The

same source further stated that food security concerns in rural households’ depend to a large

extent on the size and age structure of households’ members. The number of the households’

member capable of contributing to food production and/or who can be employed in non-farm

income earning activities will greatly determine households own production and its capacity to

acquire food through enhancing exchange entitlement.

Further, while Ayalneh (2002) explaining the feature of food insecure groups, he also implicitly

explained the factors that determine food insecurity. In that the largest group of food insecure

households’ is those who live on the edge of subsistence, often located in remote areas far from

markets. They lack the important asset of good quality land and access to productive assets. Lack

of draught power severely handicaps farmers, lack of access to credit, agricultural input and

technology. Lack of male labor in female-headed households’ is another important constraint.

They usually work in an insecure and low productivity occupation. Another determinant of food

insecurity is gender discrimination. Subordination of women in society, their over-burdening and

the greater difficulties faced by female-headed households’ contribute to food insecurity (Lathan,

1997).

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On the other hand Gezahegn (1995) explained that the major causes of transitory food insecurity

are failure in agricultural production or instability in food supplies resulting from stochastic

shocks such as recurrent draught, lack of incentives to small scale food producers, and poor

extension services for the small peasant households’. The weak system of marketing and

transport operations to procure and collect agricultural products from widely dispersed rural

producers and to distribute essential agricultural inputs on time contributes not only to the fall in

production in some years, but also to the problems caused by failure to move the available food

itself to needy areas.

Getachew (1993) in a case study of Adama Boset Using logistic regression model he showed that

there is statistically significant relationship between food insecurity and its determinants except

farming system. He also reported that there are statistically multiple relationships between

resources owned by a household and level of food security. Accordingly, it was confirmed that

amongst the sample population it is those households’ which hold land less than or equal to 3

Timads, do not own any oxen, have a small households’ adult equivalent size, are unable to use

fertilizer, and earn a non-farm income of less than Birr 500 (or none at all) which are most at risk

of food insecurity. Thus ox-ownership, level of income and land size is the most important

resources determining food security when other factors such as favorable climatic conditions and

low pest out break are satisfied. In other words, an increased size of land, ox-ownership, high

income and use of fertilizer increase the chances of maintaining food security. In his study using

logistic model of Kembata and Hadiya district Getachew (1993) tested the significance of the

relationship between households’ resources and food security. For the test he included six

variables farming systems, land size, production output, livestock, households’ size and fertilizer.

Moreover, in this study all the variables are negatively related with food insecurity except

households’ size.

2.2. Measures taken to overcome the food security problem

The government of Ethiopia has implemented a policy response specific to Ethiopia's food

security and agricultural productivity challenge, including the Agricultural Development Led

Industrialization (ADLI) strategy. This policy strategy divides the country into three main agro-

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ecological zones, which include regions with adequate rainfall, moisture stress areas, and

pastoral areas. In regions with adequate rainfall, the focus is on exerting all possible efforts to

efficiently utilize available rainwater to bring about the maximum possible rate of agricultural

development, and promoting irrigation in areas where it is feasible. In moisture stress areas,

major activities undertaken to enhance food security are focused on increasing off-farm income

opportunities, and voluntary resettlement to more productive areas. In terms of pastoral areas,

special efforts are made to enhance specialization in livestock production and marketing through

the provision of water supply for the community and their livestock as well. Major interventions

in this area also include improving livestock quality, expansion of animal health services, water

points, feed production and improvement of breeds and development of market infrastructure.

Specific policy measures practiced by the government to improve food security and show

positive results include: Agricultural extension and research, food security programme

Productive safety net programme, Voluntary resettlement Programme, water harvesting

programme, expansion of small-scale irrigation.

2.2.1 Agricultural Extension Services: A key feature of this innovative policy measure is the

employment of medium level trained extension workers to every rural kebele in Ethiopia to

facilitate sustained knowledge and skills transfer to smallholder farmers through the

establishment of Farmers Training Centers (FTCs) to transfer improved agricultural technologies

and give adequate services at a closer reach. Throughout the planning period, all of the female

headed households have access to extension services and an estimated 30% of women in male-

headed households will also get access to training and extension services in the type of

extension packages that will benefit those most. This has contributed to increased agricultural

productivity particularly for cereals, pulses, and oil seeds and decreased the number of food

insecure farmers (UN- development strategies).

2.2.2 Agricultural Research: Effective agricultural research is also at the core of improving

food security. The major outputs of the public research system are varieties with improved

agronomic and protection practices that can be used in crop and livestock diversification and

specialization, for both traditional food crops and livestock, as well as high value crops such as

vegetables, spices and other horticultural crops. Research is also conducted on food science,

19

socioeconomic and post harvest technology as well as farm implements. The research centers

maintain improved varieties and multiply breeder and pre-basic seeds and seedlings of released

varieties of crops, and distribute them to farmers. Those farmers who applied improved inputs

increased their productivity per area and decreased vulnerability to food insecurity (UN-

development strategies 2009).

2.2.3 Food Security Programme: The National Food Security Programme rests on three pillars:

increasing the availability of food through domestic (own) production; ensuring access to food

for food deficit households’ and, strengthening emergency response capabilities. But Ethiopia is

constantly dependent on international aid for nearly 10% of its annual food need. This figure at

times reaches about 25% in periods such as the drought years. This means that 4 to 5 million

people are living in continuous risk of food shortage and their existence is directly related to

external help.

The effort to reduce food insecurity problem is a central part of the PASDEP strategy. Measures

are being put in place to reduce the variance in crop production and food availability overall -

through more irrigation and water control, diversification of crops, and better integration of

markets, transport, and information links. Maintaining macroeconomic stability; expanding off-

farm employment and income-earning opportunities, and better functioning credit markets,

improving health services and nutrition, and, innovative measures, such as experiments with crop

and weather-based insurance mechanisms -are key components of these measures.

The Government tries to strengthen and expand rural micro financing institutions and

cooperatives to provide banking services especially in food insecure areas. The Government of

Ethiopia recognizes the importance of improved credit services for food insecure rural and urban

households’ in order to address both supply and demand side problems. The Government will

continue to increase the availability of rural financing and provide special support in reducing the

credit administration cost extended to food insecure communities. Cooperatives are expected to

play a big role in this regard.

Furthermore, the Government has gradually shifted away from food assistance (assistance in

kind) towards financial assistance for the purchase of food from the domestic market. This has

20

helped augment the stocks of food security reserve in good times. This in turn contributed to the

creation of effective demand through stabilization of prices.

Since the launching of the Programme, remarkable achievement has been made in narrowing

overall food gap from domestic production. The recent report by the Disaster Prevention and

Preparedness Agency (DPPA) shows that the number of people requiring emergency assistance

stood at 2.3 million in 2010/11from5.2 million in 2009 /10, evidence that the food security

situation in the country has improved significantly (FEWS NET 2010).

2.2.4 Productive Safety Net Programme: The Productive Safety Net Programme is intended to

bridge the income gap of chronically food insecure households and engage such households in

community asset building efforts especially during the lean season and times of drought. Priority

for households’ asset-building interventions is given to beneficiaries of the Safety Net

Programme.

The programme started in 2005 and covers 287 woreda. It has two components - labor-intensive

public works and direct support for labor-poor households’. The able-bodied are engaged in

public works for which they are paid a minimum amount, while the labor poor are provided the

same amount free. A key feature of the Safety Net Programme is its households’ focus. It is

linked to the households’ asset-building efforts of the Food Security Programme in that the

priority for households’ asset building interventions is assigned to those covered by the Safety

Net Programme, as they are the chronically food insecure. The Safety Net Programme through

its predictable transfer of resources will help prevent asset depletion, which is an important

factor for the attainment of food security. This is in addition to the community assets it helps

build.

2.2.5 Voluntary Resettlement Programme: Over the years, a large portion of the country's

population has lost the productive capacity mainly due to land degradation and high population

pressure, while at the same time Ethiopia has a considerable amount of land suitable for

agriculture currently under-utilized. To rationalize resource use, and thereby help food insecure

households’, the Government is supporting voluntary resettlement as part of its food security

21

programme. To date, over 149,000 households’ have been resettled. Resettlement is on a purely

voluntary basis, and each settler households’ is guaranteed a package of assistance that includes

provision of up to 2 hectares of fertile land, seed, oxen, hand tools, tools, and food rations for the

first eight months. Settlers are also provided access to essential social infrastructure (clean water,

health post, feeder road), and logistics support.

2.2.6 Water harvesting:- In the area of water harvesting, the technique is considered to be one

of the major interventions to overcome the challenges of households’ food insecurity in the

country. In this regard, efforts are in progress to construct water-harvesting structures across the

country. Water harvesting schemes are generally viable, with an economic rate of return of

32.7%, and an annual earnings of about ETB 6,400 households’ /annum. Accordingly, 139,462

different types of water harvesting structures with different capacities have been constructed in

the four major regions. These structures are at households’ level and are meant for life saving

irrigation for field crops as well as for vegetable gardening where conditions are favorable.

Extension and training programmes are also designed to pay particular attention to enhancing

farmers' capacity to use water resources efficiently, and to boost productivity for both

households’ consumption and for market.

2.2.7 Expansion of Small-scale irrigation: The most direct and significant contribution to an

improvement in food security for rural households’ has been made by the support furnished for

small-scale irrigation development. Some 31,000 households in densely populated drought-prone

areas have been reached through the support provided for small-scale irrigation projects, and

many of these households are gradually seeing an improvement in their incomes. Findings

suggest that increases in crop yields over the traditional yields are in the range of from 25 to 40

percent, and in cases where irrigation facilities have been built around springs, the increases have

been between 75 and 100 per cent. Thanks to these irrigation developments, the targeted

irrigation farmers’ physical and financial assets have started to increase, although experience

suggests that it may take six or more years for irrigation farmers to experience the full benefits

(IFAD 2009).

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2.2.3 Main challenges that affect the success of food security:

The extent of the food insecurity has become sound the alarm. As much as 45 percent of the

population is affected during drought years. The serious and accelerating problems of food

insecurity in Ethiopia are now considered a national security threat. So breaking the cycle of

food insecurity problem has remained one of the difficult challenges towards poverty reduction

in Ethiopia. Factors that may aggravate the situation are:-

2.2.3.1 Climate change: is an immediate and unprecedented threat to food security of millions

of households’ that depends on small-scale agriculture for their livelihood. Climate change in

Ethiopia affects all four dimensions of food security: Food production and availability, stability

of food supplies, Access to food and Food utilization. ILRI (2006) and Stige et al. (2006)

identify Ethiopia as one of the most vulnerable countries to climate change. Climate affects food

production directly through changes in agro-ecological conditions and indirectly by affecting

growth and distribution of incomes, and thus demand for agricultural produce. Greater

fluctuation in crop yields and local food supplies can adversely affect the stability of food

supplies and food security. Climatic fluctuations will be most pronounced in semi-arid and sub-

humid regions and are likely to reduce crop yields and livestock numbers and productivity which

increase vulnerability. Climate change decrease access to food due to food price increases and

declining rates of income growth. Climate change may initiate a vicious circle where infectious

diseases, including water-borne diseases, cause or compound hunger, which, in turn, makes the

affected population more susceptible to those diseases. Results may include declines in labour

productivity and an increase in poverty, morbidity and mortality (Schmidhuber and Tubiello

2007).

2.2.3.2 Technology adoption problem: The country extension system inability to transmit

improved technology and farming practices to producers in participatory and accountable ways

worsen the food insecurity. Over the years, many development agendas and practices were

prescribed in a top-down approach to the rural people and farmers. Potentially well designed

programs and practices usually failed simply because farmers were not given the chance to ask

“why”, “where”, “how” and “when” they should adopt these practices. Extension workers

23

mandated to persuade or teach farmers at grassroots level are quite often practically unskilled or

even irresponsible.

2.2.3.3 Rapid and unhindered population growth: “ Rapid and unhindered” population growth

is a significant factor in exacerbating food shortages in Ethiopia – the second most populated

country in Africa – according to a 2009 report by the UN Emergencies Unit for Ethiopia. That

year, 20 percent of the population was dependent on foreign-supplied food aid. Of the country’s

current 80 million people, an estimated 12 million Ethiopians are facing serious threats from

food insecurity and famine. More than half of the country’s children under five years of age are

stunted in growth and 47 percent are underweight. With one of the highest birth rates in the

world, Ethiopia’s population is projected to increase by 20 million in the next 10 years and

double by 2045. Forty-five percent of the population now is under age 15. Each Ethiopian

woman gives birth to an average of six children, and 36 percent of married couples that desire to

use contraception to space or limit childbirths do not have access to contraceptives. Population

growth is putting unprecedented and increasing pressure on vital natural resources, including

cropland and fresh water. Dozens of countries already have reached alarmingly low levels of

available cropland. Currently, 17 million people live in countries with less than 0.5 hectare of

cropland per person – the minimum cropland capable of supplying a vegetarian diet for family

(starvation plot).

2.2.3.4 Poor input and output market system: Lack of efficient and effective input and output

market systems is a major obstacle to the Ethiopian agriculture and food security. In Ethiopia,

surplus food may be produced in some parts of the country, but because of weak transport and

market links it cannot be easily transported to food deficit areas. The country’s high transport

costs and poor infrastructure aggravate the food insecurity situation for poor farmers. Studies on

the grain market (Mulat et al. 1998) and input use confirm the existence and consequences of

these problems. Improvement in market policy and investment in infrastructure is necessary to

reduce food transaction costs and enhance the incentive to produce more and improve food

security situation in the country.

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2.4 Empirical Literature

Food insecurity could be caused by several factors. Following the usual practice, we classify

them into two broad categories- immediate and underlying community conditions. Under

immediate conditions, we have low rates of agricultural production; low access to food resulting

from low income; poor roads and infrastructure facilities. On the other hand, underlying

community conditions include existing factors which could interrupt availability, accessibility,

utilization, and stability of food. For example, if a community is characterized by poor

infrastructural conditions, productive capabilities of farmers could be hampered as they will have

limited access to new technologies, to credit, and also to storage and transportation facilities for

inputs and outputs. Subsistence farming is also characterized by low yield and growing levels of

soil fatigue as people remain in one area for extended periods and become less peripatetic than in

the past.

The food security status of the community could also be affected negatively by bad local and

international market conditions which could result from ill-designed domestic and international

trade policies. These could reduce access to food by the community from local as well as outside

sources. In addition, the food security status of the community could be frustrated by HIV and

AIDS and other pandemics that harm economically productive sections of the society.

Studies show that food prices have increased sharply over the past five years. This has been

attributed to a number of factors: rising energy prices and subsidized bio-fuel production; income

and population growth; globalization and urbanization; land and water constraints

underinvestment in rural infrastructure and agricultural innovation; and lack of access to inputs

and water disruptions (FAO, 2008). This has made poorer households’ highly vulnerable to food

insecurity by decreasing their purchasing power. Food constitutes the lion’s share of poor

households’ expenditure or budget.

Study made in Zimbabwe on determinates of households’ food security in the semi-arid areas of

lupine and hwange districts by (Misery Mpuzu 2008) using logistic regression conclude that

having access to irrigation by communal farmers has a positive and significant effect on

25

households’ food security. Farmers who are on irrigation schemes are more likely to be food

secure than dry land farmers. Thus, the hypothesis “Irrigation farming in communal areas

enhances households’ food security” is accepted. Access to irrigation does not only increase crop

production but also increases incomes that can be used on non-farm goods and services. The

same study further found that lack of access to credit and cash crop production displace food

crops and households’ consumption of own production is reduced. Thus the households’

vulnerability to food insecurity tends to increase. However another study in Malawi by Diagne

.A. (1998) found that formal credit has marginally beneficial effects on households’ annual

income. However, these effects are very small and do not cause any significant difference

between the per capita incomes, food security, and nutritional status of credit program members

and non-current members.

Choosing timing and volume of maize harvest as an indicator (Shiferaw T.Feleke 2005) in

southern Ethiopia to assess determinates of food security by using regression model: he found

that based on results from tests of the full/reduced models and the magnitude of changes in

conditional probabilities of food security, he conclude that the supply-side variables are more

powerful than the demand-side variables. Results also show that an increase in per capita

aggregate production is not necessarily translated into households’ food security at the

households’ level. The study highlights the deterioration of rural households’ food security due

to the income effect of declining prices associated with increased per capita aggregate

production. The same study also future confirmed that based on the positive and significant

relationship between technology adoption and households’ food security, adopters of improved

technology are more likely to be food secure than no adopters. Since the effect of technology

adoption can be explained through increased income, it can be argued that technology adoption

can also have an important effect on the distribution of benefits through increased demand for

nonfarm goods. Although the study shows that technology adoption improves households’ food

security through increasing food availability or households’ cash incomes in the short run, we

cannot infer that this positive relationship will hold in the long run or at the macro level. This is

because with increased adoption of improved technologies, the proportion of marketed surplus

will generally increase, as non adopters become adopters. However, given a very low overall

price elasticity of demand for cereals in developing countries, the increase in marketed surplus

26

causes prices to fall further, and eventually makes the producers worse off. This was inferred

based on the negative relationship between per capita aggregate production and households’ food

security.

Studies done to assess determinates of households’ food security(Bartfeld & Dunifon, 2006;

Kidane, Alemu, Khundhlande, 2005; Shiferaw, et al. 2005; Abebaw & Ayalneh, 2007) found

that demographic factors also play a influential role in households food security status.

households’ whose heads are educated are often more likely to be food secure; on the contrary,

households’ with relatively more mouths to feed (i.e. with a higher dependency ratio) are more

likely to face food insecurity (Bartfeld & Dunifon, 2006; Shiferaw et al. 2005; Abebaw &

Ayalneh, 2000); women-headed households’ face gender specific obstacles, adversely affecting

their ability to produce food (FAO, 2008; Bartfeld & Dunifon, 2006). And even if they are

employed, they don’t earn as much as their male counterparts. They also spend much of their

time doing unpaid work in the households’ and chances are slimmer for households in affluent

neighborhoods (higher income earners) to be food insecure (Bartfeld & Dunifon, 2006; Kidane,

et al., 2005; Shiferaw, et al. 2005).

Amhara regional state of Ethiopia, the case of North Wollo, the data analysis was based on food

balance sheet and aggregate food security index reveal that the north wello zone is highly food

insecure area and the majority of the sampled households’ depends on famine relief assistance.

In addition they tried to find the cause of food insecurity using logit model and found that cereal

production, education, fertilizer consumption, livestock, land size, reduce the probability that

households’ food insecure while, family size increase the probability of insecurity (Ramakrishna

et al 2002).

Off-farm employment opportunities in rural Ethiopia are limited in both availability and income-

generating potential. Only 44% of rural households’ surveyed by the Ministry of Labor in 1996

reported any non-agricultural sources of income and these contributed only for 10% to

households’ income (Befekadu and Berhanu 2000). Another survey in Hararghe Region

confirmed that off-farm activities generated only petty incomes: women collect and sell firewood

and forage, men and women seek irregular, low-paid work as farm laborers, and some men

27

migrate seasonally (ICRA et al. 1996). In a survey conducted in the Amhara region, 25% of

households’ had one or more members migrate during the dry season in search of work, mostly

to nearby rural areas. One in three migrants had difficulty securing employment, while half

brought back no food or income for their families (FSCO 1999).

A number of studies have been taken by (Bigsten A, Kebede B, Shimelis A and M

Taddesse2007, Dercon S 2006, MoFED 2006) to examine the determinants of food security and

poverty in rural areas of Ethiopia using logistic regression and found that. Socio-economic

variables such as asset holding (mainly cultivated land, farm income and livestock holding) and

access to services like credit are found to be important correlates which affect households’ food

security favorably. While controlling for all other variables, households’ with better access to

irrigation are found to have significantly higher wellbeing and so more likely to be food secure.

However, among demographic variables considered in this study only households’ size was

found to have a negative and statistically significant effect on households’ food security.

Contrary to usual expectation, the coefficient of education level of the households’ head was not

statistically significant. This may imply that education of households’ head has not yet enhanced

households’ capabilities to adopt better production technologies, accept technical advice from

extension workers and diversifying their source of income than the illiterate ones which would

have reduced the risk of food insecurity among households. The results also suggest that both

food secure and food insecure households’ have the same access to food aid resources.

2.5 Methodologies of measuring food security

The next section outlines four ways of measuring households’ food security outcomes: individual

intakes, households’ caloric acquisition, dietary diversity, and indices of households’ coping

strategies. This ordering of methods is deliberate, moving from methods that are very time and

skill-intensive but are regarded as being more accurate, to those that can be implemented

quickly, are relatively undemanding in terms of the skills required by the implementers, but are

more impressionistic. In this study households’ caloric acquisition will be applied.

28

2.5.1 Households’ Caloric Acquisition: This is the number of calories, or nutrients, available

for consumption by households’ members over a defined period of time. The principal person

responsible for preparing meals is asked how much food she prepared over a period of time.

After accounting for processing, this is turned into a measure of the calories available for

consumption by the households’ (John Hoddinott 1999).

2.5.2 Methods for generating data: A set of questions regarding food prepared for meals over a

specified period of time, usually either 7 or 14 days, is asked to the person in the households’

most knowledgeable about this activity(John Hoddinott 1999). There is no consensus regarding

the optimal recall period between 7 and 14 days. In our experience, 7 days seemed to be the most

appropriate. A shorter recall period would have risked missing foods served infrequently, say on

Fridays (in Muslim areas) or Sundays (in Christian areas). A longer recall period has proved

problematic as difficulties of remembering what was prepared appear to increase. However,

other organizations such as the World Bank in its Living Standard Measurement Surveys have

used the 14-day recall period.

In constructing these questions, the following considerations should be borne in mind: it is

extremely important that the list of foods specified in the questionnaire is detailed and

exhaustive. Experience has shown that using short lists typically leads to an understatement of

consumption on the order of 25 to 75 percent (Deaton and Grosh 1998); the phrasing of the

questions needs to be unambiguous in the sense of distinguishing between the amount of food

purchased and the amount prepared for consumption and the amount of food served; and it is not

uncommon for individuals to report consumption in units other than kilograms or liters. In such

cases, it is necessary to obtain information on the size of a "kirchat" or the quantity contained in

a "Silicha" or whatever units are used locally.

2.5.3 Advantages of this method: This measure produces a crude estimate of the number of

calories available for consumption in the households’. It is not obvious to respondents how they

could manipulate their answers. Because the questions are retrospective, rather than prospective,

the possibility that individuals will change their behavior as a consequence of being observed is

29

lessened. The level of skill required by enumerators is less than that needed to obtain information

on individual intakes. On average, it took around 30 minutes per households’ to obtain these

data, an amount of time considerably less than that required to obtain information on individual

intakes (John Hoddinott 1999).

2.6 Expected Contributions of the study

Ethiopia is an agrarian economy with more than 80 percent of its people dependent on

agriculture. The Government of Ethiopia has been trying to achieve food security at both

households’ and national level through these small-scale farmers. Identifying determinates of

households’ food security has been studied by many researchers in the country. This study

focuses on assessing determinates of households’ food security in Kamba woreda in which no

similar research has been done. Methodological gap and variables not included in previous

studies were taken as the gap that this research going to fill. Various factors contributing to

households’ food insecurity will be discussed so that recommendations can be made for better

strategies and actions to assist small-scale producer farmers to address households’ food

insecurity challenge in the study area.

2.7 Comments on the Reviewed Literatures

Much of the reviewed literature on household food security concentrated on describing

qualitatively and quantitatively the extent of household food security and identifying the factors

and examining their implications. Almost all reviewed studies applied logistic regression in

modeling relationships between variables. However, the central task of regression analysis: the

parameter estimation techniques and variable selection methods were not addressed. Most of the

reviewed model did not check model adequacy: detection and treatment of outliers, influence

diagnostics and multicollinearity. Almost all reviewed studies did not examine the sustainability

issues in detail. Hence, in this study in addition to the prediction, a sustainability issues will be

used taking into account the limitations described in the reviewed literature.

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CHAPTER THREE

RESEARCH METHODOLGY

3.1 Description of the Study Area

The study area, Kamba woreda, is found in Gamo Gofa zone, which is located in the Southern

part of SNNPR. Wolayta and South Omo administrative zones border the zone in the north and

south, respectively. Kamba is one of the 15 administrative woreda of Gamo Gofa zone. It is

bordered by Bonke woreda in the East, Zala woredas in the West, Daramalo woreda in the North

and South Omo zone in the South.

According to annual report of the Office of Agriculture (2002), Kamba has an estimated total

land area of 118,054 hectares of which only 50,787 hectares are arable. From arable land 20,345

hectares are used for annual crops 2,722 hectares are used for perennial crops and 27,720

hectares of arable land is the potential for the future and 22,364 are forest covered 27,664 are

pasture land, and 5,300 are unclassified. The woreda has nine big rivers of which three of them

have been used as source of modern irrigation.

Kamba, the capital of the woreda, is located 105 Kms from the zonal capital, Arbaminch and 635

kms away from Addis Ababa. The agro-ecological classification of this woreda consist of low

lands(kola), middle altitude(weynadega) and high lands(Dega).The woreda has 27% mid-

altitude,28% highland and 45% lowland agro-ecological zone. The top of the escarpment is

approximately 3340 m.a.s.l and the foothills and ridges raise to700 m.a.s.l

3.2 Livelihood Strategies in the study area

Mixed farming, both rain fed and irrigation based, agriculture is the primary source of livelihood

with mainly maize, wheat, sweet potato and enset grown as staple food crops, vegetables

predominantly onion and Shiferaw, coffee and corerrima are some of perennial cash crops.

However, even though all these crops are grown in the area, the livelihood of the farm

households’ heavily depend on the success and failure of maize production. The other important

livelihood activity, which plays an indispensable role in the mixed farming operation, is

31

livestock production. Of the different livestock species in the production system holders pay

greater emphasis to the large and small ruminants, cow, ox, sheep and goat, production. Because,

their capacity generate income in a shorter period is very high. In other words, a household who

has large number of livestock, especially chattels, deserves greater respect and influential power

in the locality.

3.3 Population

Based on the 2007 population and housing census results the Gamo Gofa zone has a total

population of 1,595,570 (CSA, 2007). From this, 1,436,601 (90%) of the population lives in the

rural areas depending on agriculture, while the remaining 106,234 (10%) lives in the urban areas.

The population distribution of Gamo Gofa zone is the combined effect of temperature, rainfall,

and soil fertility. The central highlands of the zone that have enough rainfall and other suitable

natural conditions for cultivations support large number of population. On the other hand, the

surrounding lowland, which is characterized by insufficient rainfall, high temperature, and higher

incidence of diseases such as malaria has very small number of population or sparsely populated

(2007). Hence, population distribution in Gamo Gofa is uneven. According to the same source,

the average population density of the zone is 85 persons per Km2. Children less than 15 years

accounts for 46.9%, the economically active population aged 15 to 64 accounts for 50.9 % and

those aged 65 and above constitute 2.18%. Thus about half of the population of the zone is under

the category of the independent age group. However, the dependency ratio of the zone in terms

of percentage is 97, which is quite high.

The total population of the study woreda is 155,748 of which 49.2% are women and 50.8% are

men (CSA, 2007). According the same source, children whose age is 14 or less account for

46.1%, this is similar to the situation in the zone average. Economically active population ages

between 15 and 64 accounts for 51.6% and those aged 65 and above are 2.3 %, which is also

similar to the zone average. According to Gamo Gofa Planning and Economic and Development

Office (2001), the average households’ size of the zone was 6.34, which is more than the

national average of 5. And, the average households’ size of the study area is 6.65, which is more

than the zonal average. The average population growth rate in the study area is also above the

32

country average growth rate (2.8% CSA, 2006). Table 1 shows the woreda population growth

rate in the past ten years as compared to country growth rate.

Table 1: - Population growth rate of Kamba woreda

Growth rate Growth rate

Year Kamba Country Year Kamba Country

2001 3.4 2.65 2006 3.0 2.60

2002 3.8 2.62 2007 5.2 2.59

2003 3.0 2.60 2008 3.2 2.59

2004 3.2 2.56 2009 3.4 2.58

2005 3.2 2.56 2010 2.9 2.45

Source: - World Bank2008 report and Kamba Woreda council

3.4 Religion

Religion in the woreda is classified and presented in Table 2. As it is indicated in the Table,

majority of the population are Protestants (about 58%). Next to Protestant Orthodox Christian

accounts about 24.5 percent and households’ with no religion 16%. There is no conflict among

different religion followers. Therefore, food security problem due to religion conflict is not

observable. Food source and feeding habit of all religion is basically similar

Table 2:- Religion distribution of the study area

Religion Percentage

Orthodox 24.5% Protestant 58% Muslim 1.5% No religion 16%

Source:-Woreda council 2010/11

3.5 Agriculture

As elsewhere in the country, agriculture is the major occupation of people living in the study

woreda. Except for few, the livelihood of the population (residents of both rural and urban areas)

in the woreda depends directly or indirectly on agriculture. More specifically, agricultural

production (livestock and/or crop production) is the main source of income and employment to

the society, though the degree of importance varies from one Keble to another.

33

The farming system of the study woreda is governed by the agro-ecology of the area, which

consists of highlands, midlands, and lowlands. In the highlands, mixed farming is practiced

which cultivate cereal as their annual major crop and enset as their perennial crop and animal

rearing as their minor on-farm activities. In the midlands, mixed farming is also practiced but

their main farm activities are cash crop and animal rearing. In the lowlands, mixed farming is

also common farming practice but focusing on maize production and animal rearing as major

activities. Pastorals depend strongly on animal rearing and to some extent on sorghum farming.

3.6 Crop Production

The major crops produced in the Gamo Gofa zone in general and Kamba woreda in particular are

cereals, roots and tubers, vegetables, and fruits and spices. Maize, wheat, barley, and teff are the

dominant cereal crops and sweet potato, Irish potato and enset are also the dominant roots and

tubers produced in the woreda. Coffee and coriander (corerrema) are also mostly produced

spices. The distribution of these major crops varies from place to place depending on crop

suitability factors (soil, rainfall, temperature, etc). For example barley, wheat and Irish potato are

cool weather crops, and are predominantly grown in the highlands above 1500 m.a.s.l where the

average annual rainfall ranges from 1000 mm to 2000 mm. Maize and sorghum are warm

weather crops they grow under rainfall of 800 mm to 1500 mm in midlands and lowlands. Pulses

such as haricot bean and field peas are widely grown in the study woreda and usually

intercropped with maize, sorghum and perennial crops like enset and coffee.

3.7 Livestock and Poultry Production

According to Kamba woreda Agricultural Development Department (2002), the Worde’s total

population of livestock and poultry is estimated to be 338,011. Among this, cattle population

accounts for 107,338(32%), followed by poultry 94,686(28%), sheep 78,368 (23%) and goat

45,796(13%). The proportion of the horses, donkeys, and mules are 2.5, 0.5 and 1percent

respectively. Here, cattle are the major source of farm power for plowing, threshing as well as

for manure supply. The highest concentration of goats is found in the lowlands of the woreda

where pastoralists live. Largest number of sheep and equines are mainly found in the highlands

because of disease problem in the lowlands. According to zonal agricultural department annual

report (2002) the study area is the main sources of meat livestock’s, especially for oxen and got.

34

3.8 Agricultural Extension

Agricultural extension is one of the most important inputs, which encourages farmers to use

improved techniques and creates an enabling environment for agricultural input and output

markets in the case of Gamo Gofa in general and Kamba woreda in particular. Agricultural

extension focuses on use of improved hybrid seeds, fertilizer, animal husbandry, and soil and

water conservation to increase farmers’ productivity. The agricultural extension serves in the

woreda also focus mainly on crops, livestock and natural resource development activities.

There are118 Development Agents (DAs) serving 23,420 farming households’ in Kamba woreda

(WoA, 2002). The development agents have diploma level education and recruited from the

community and live within the community to provide extension services. The ratio of

households’ to DA in the study area is 1:198. This ratio is more than double compared to the

national ratio of 600. This is one of the issues to be considered.

3.9 Input Supply

Key agricultural inputs used by farmers in Kamba woreda are improved seeds, chemical

fertilizer, improved chicken and protection chemicals. Improved seeds include maize and wheat.

Chemical fertilizers commonly used are DAP and urea. Plant protection chemicals are pesticides

and herbicides. The ten years average of fertilizer use in the woreda is 825 quintals DAP per

annum and 19 quintals of urea (WoA 2002); the quantity used per households’ is almost 3.5kg

of DAP and very small amount of urea per households’ which is too small to bring about a

change in production of the woreda in general (WoA 2002).

3.10 Rural road Road network is not well developed and the majority of the existing roads are not in a position to

function in wet seasons. Due to this problem the movement throughout the woreda is restricted

and the development effort is hampered. Until the year 2003 there were a total of 48km of roads

in the woreda out of which only 20 km were RR-10 standard roads all weather rode. According

to Kamba woreda council road network problem has been number one problem in the study area

for the problem of food security. Food transportation is very costly and farmers and consumers in

the study area pay abnormal price during normal production seasons.

35

3.11 Market There are three dominant and high monetary exchange market places located in open rural

villages. These markets are traditional in nature and are characterized by inadequate marketing

facilities and services. Particularly, feeder roads and roads linking rural areas with urban

consumption centers are inadequate. Thus, the majority of the areas are inaccessible by vehicles

making it imperative to use pack animals (such as donkeys).

3.12 Unexploited opportunities that exist in the woreda

Agriculture and livestock development are almost certainly the only viable alternatives for

improving the food security status of kamba poor majority people. Kamba district has three

constructed irrigation scheme covering 470 hectares and there are more than four big rivers

feasible for irrigation scheme with potential covering about1,200 hectares. The woreda has one

of the largest livestock populations in the zone and Kamba woreda is the known supplier of meat

livestock’s. According to Kamba woreda tax office report in each year averagely 8,000 oxen and

15,000 goats have been transported from the woreda for export or local consumption. The

woreda has all the three agro-ecologies and known coffee producer next to Mallo woreda in the

Gamo Gofa zone. The woreda agricultural office report shows that about 13,456 hectares are

suitable for coffee and Correrima production. In the highland farmers are producing highland

fruit, especially apple. The woreda has 27,720 hectares arable land which is suitable for

agriculture and still not owned by farmers.

3.2 Methods and Sources of data collection

3.2.1 Methods of data collection

A detailed households’ survey was conducted to collect both primary and secondary data on the

dimensions of food security and livelihood strategies in Kamba woreda. The woreda has three

agro-ecological zones Dega (14PAs), Woynadega (10PAs), and Kola (14PAs).The data collection

was done efficiently through a structured questionnaire to collect the required data from selected sample

households’ during the 2010/1011 production year. The questionnaire was first pre-tested and modified

before the execution of the survey (See the questionnaire in Appendix 4). For this study Development

agents (DAs) wear used to collect primary data after two days training on the questionnaires,

selection was based on their work performance, their ability to local language and their interest

36

to collect the data in the selected PAs. To ease and keep uniformity among enumerators,

standardizing unit on local measurement of different food items and codes for some questions

were provided to each enumerator. The enumerators who are stationed in the survey areas

administered the structured questionnaires under the continuous supervision of the researcher. The survey

was carried out on March 2011. The primary data were supplemented by secondary data whenever

necessary from governmental organizations.

Sample Size Determination:-There are several approaches to determine the sample size. These include

using a census for small populations, imitating a sample size of similar studies, using published tables,

and applying formulas to calculate a sample size. This study applied a simplified formula provided by

Yamane, (1967) to determine the required sample size at 95% confidence level, degree of variability = 0.5

and level of precision =9%.

n = ------------------------------------------------- (1)

Where n is the sample size, N is the population size (total households’ size), and e is the level of

precision. The above formula required a minimum of 123 responses but this study was carried out on 200

respondents.

Sampling Technique:-For this particular study a two-stage random sampling procedure was

implemented to select 200 rural households’ in the woreda. To increase the precision of estimates

households’ were stratified by agro-ecological zone of the peasant associations (PAs) they live

in. At the first stage, 13 peasant associations (PAs) were selected randomly out of 38 PAs which

constitute about 34% of the total PAs in the study area. Thirteen PAs wear selected by applying

size to agro-ecology proportionality across the three zones. This was done by selecting 34% of

the total PAs in each zone, by doing this from both “Kola” and “Dega” zones 5 PAs were

selected randomly and from “Woynadega” 3 PAs were selected also randomly. In the second

stage, considering the PAs households’size, random selection of households’ equal to probability

proportional to households’ size sampling technique was employed to draw sample households’.

From randomly selected PAs maximum 34 households’ from larger kebeles and 10 households

from smaller kebeles were selected and in each kebele two reserve households selected

randomly, if the households’ is not present in the kebele at the time of interview.

37

At the second stage of sampling, sample frame (tax payment list for land holding) was applied to

pick out targeted households’ using lottery system. Responses from 200 households’ were

however found useful for this study. Secondary data was mainly collected from woreda

government offices.

The questionnaire helped to draw out information related to the different aspects of the

households’ and individual characteristics including: households’ food habit and consumption,

households’ demographic and socio-economic characteristics, consumption pattern, households’

income and expenditure, labor input in agriculture and non-agricultural activities, crop and

livestock production, farming systems and productive resources, land use, access to services,

access to infrastructure, amount of farm and off-farm income as well as coping strategies

employed by the households during time of food shortage. Before analysis of households’ data

was started, quantity of each item consumed during the last seven days were converted into their

equivalent kilocalorie using ENHRI food composition table for use in Ethiopia (ENHRI 1968-

1997) and households’ members to their adult equivalent(see appendix 3).

3.2.2 Method of data analysis

Food security at households’ level is best measured by the direct survey of dietary intake (in

comparison with appropriate adequacy norms). The level of, and changes in socio economic and

demographic variables can be properly analyzed, and can serve as proxies to indicate the status

of and changes in food security (Von Braun et al, 1992).

A set of questions regarding food prepared for meals over a specified period of time, for this

study for the last seven days, excluding interview day meals was asked to the person in the

households’ most knowledgeable about this activity and other socio-economic and demographic

data’s wear also used to analyze data. The response on food consumption was changed to

international unit (if local unit was used) and converted to calorie availability and compared with

calorie demand or minimum calorie requirement. The government of Ethiopia has set the

minimum acceptable weighted average food requirement per adult equivalent (AE) per day at

2100 kcal. The determination of the adult equivalent takes into account the age and sex of each

38

household’s member (Gassmann F and C Behrendt 2006) (see appendix 3). Hence, for this study

2100 kcal per adult equivalent per day was employed as a cut-off value between food-secure and

food-insecure households’.

Once the groups wear categorized as food-secure and food-insecure, the next step was to identify

the socio-economic factors that are correlated with food security. A variety of statistical models

can be used to establish the relationship between these households’ characteristics and food

security. Conventionally, linear regression analysis is widely used in most economic and social

investigation because of availability of simple computer packages, as well as ease of interpreting

the results. However, results derived from linear regression analysis may lead to fairly

unreasonable estimates when the dependent variable is dichotomous (Ayalneh Bogal and A.

Shimelis volum9 No9 2009).Therefore, the use of the logit or probit models is recommended as a

universal remedy of the drawback of the linear regression model (Gujarati DN Basic

Econometrics, Fourth edition. McGraw- Hill, New York 2003).Which model to choose between

logit and probit is, however, difficult for they are similar in most applications, the only difference

being that the logistic distribution has slightly fatter tails. This means that there is no binding

reason to choose one over the other but for its comparative mathematical and interpretational

simplicity many researchers tend to choose the logit model (Hosmer DW and S Lemeshew

Applied Logistic Regression New York. 1989). Therefore, this study applies the logistic

regression model due to dichotomous behavior of dependent variable.STATA10 package was

also used to see the dominant factors that significant affect food security in the study area.

3.3 Theoretical model

Gary Becker’s idea about family economy, households’ production function and family time

allocation is the inspiration of agricultural households’ models (Becker, 1965). Agricultural

households’ is a worker, a producer and a consumer all together, with his ultimate aim of

maximizing utility. The models can also be used to address consumption and related nutrition

policy issues (Strauss, 1984). The existence of imperfect market is common in the LDCs; one

common cause of market imperfection is the existence of transaction costs. For the same food

product, households’ typically sells it for a lower price than the price at which he can purchase in

39

the market. Thus, it is the budget constraint for the agricultural households’. With this budget

constraint in mind, we have a clear picture of utility maximization for the agriculture

households’.

In Ethiopia, a households’ food security model was used to look at the importance of the supply

side against demand side variables in determining households’ food security in Southern

Ethiopia (Feleke et al., 2005). From the results, it was established that the supply side variables

are more powerful determinants of households’ food security than the demand side variables.

The extent of households’ food security in this study will be modeled within the framework of

consumer demand and production theories following the modeling of production and

consumption behaviors of a rural and Agricultural households’ models by Singhand

Shiferaw(1986) and T. Feleke (2005). Following Agricultural households’ models 1986 by

Singhand Shiferaw and T. Feleke 2005, the households’ utility function is specified as:

U = U (Fi, Fm, L; Dh) -------------------------------------------- (2)

s.t

G (Qi , L, A0, K0) = O

PmFm = Pi (Qi - Fi ) - w(L-Lf) + N=0

T=Lf + ℓ

Where U is a utility function that is assumed to be well behaved (twice differentiable, increasing

in its arguments, and strictly quasi-concave); Fi is a vector of home-produced goods and

consumed by the households’; Fm is a vector of market-purchased goods consumed by the

households’; and L is leisure. The utility that the households’ derives from various combinations

and levels depends on the preferences of its members, which are shaped by the characteristics of

the households’, Dh.

40

As indicated in the Agricultural households’ Models 1986 by Singhand, Shiferaw and T. Feleke

2005, the households’, as both producer (firm) and consumer, is assumed to maximize its utility

from the consumption of these goods subject to farm production, income, and time constraints

specified as

where G(·) is an implicit production function that is assumed to be well behaved (twice

differentiable, increasing in outputs, decreasing in inputs, and strictly convex); Qi is a vector of

quantities of goods produced on-farm; L is total labor input to the farm; A0 is the households

fixed quantity of land; K 0 is the fixed stock of capital; Pi is the price of good i; Pm is the price of

a market-purchased good; (Qi−Fi) is the marketed surplus of good i; w is the wage rate; Lf is the

households’ labor supply for on-farm use; N is nonfarm income that adjusts to ensure that Eq.(3

) equals zero; and T is total time available to the households’ to allocate between work and

leisure. The income and time constraints can be combined by incorporating the constraints

equations.

PmFm = Pi (Qi – Fi) – w (L –T + ℓ) + N …………………… (3)

Rearranging Eq. (3) gives

PmFm + PiFi + wℓ = PiQi + wT – wL + N …………………(4)

The left-hand side of Eq. (6) is the households’ expenditure on food and leisure, and the right-

hand side is the full income equation. The expenditure side includes “purchases” of its own farm-

produced good i (PiFi), the households’ purchases of the market good (PmFm), and the

households’ “purchases” of its own leisure time (wℓ). The full income side consists of the value

of total agricultural production PiQi, the value of the households’ entitlement of time wT, the

value of labor on the farm, including hired labor wL, and nonfarm income N.

From the first-order conditions of the maximization of the constrained utility function, the

relationship between production and consumption can be established in such a way that

production decisions are made first and subsequently used in allocating the full income between

41

consumption of goods and leisure (Strauss, J., 1983).This is based on the assumption that all the

relevant markets function. It is important to have this assumption because we are considering

that consumption (food security) depends on the production variables, but not vice versa. If the

markets for inputs, product, and labor do not function, farm production decisions cannot be made

separately from the consumption decisions. When a commodity has an incomplete market, or if a

households’ is at a corner (i.e., if it consumes all of its output), there will exist a virtual (or

shadow) price, which will be endogenous to the households’ (Singh et al., 1986).

Given the assumption of separability between the production and consumption decisions, Pi and

Pm are exogenous, the utility function to be well-behaved. We can mathematically derive the

production-side and consumption-side equations separately. Starting with the production side,

the first-order conditions can be solved for input demand (L*) and output supply (Q*) in terms of

all prices, the wage rate, fixed land, and capital as

L* = L* (Pi, w, A0, K0), --------------------------------------------------- (5)

and

Q* = Q* (Pi, w, A0, K 0), ------------------------------------------------- (6)

These solutions involve the decision rules for the quantities of labor input used and outputs

produced (production side). Once the optimum level of labor is chosen, the value of full income

when profits have been maximized can be obtained by substituting L* and Q* into the right-hand

side of the income constraint (Eq. 6) as

Y* = PiQi* + wT – wL* + N ------------------------------------------- (7)

and

Y* = wT + π*(Pi, w, A0, K0) + N ---------------------------------- (8)

42

Where Y* is “full” income under the assumption of maximized profit π*.

The first-order conditions can be solved for consumption demand in terms of prices, the wage

rate, and income as

Fk = Fk (Pi, Pm, w, Y*), ------------------------------------------------- (9)

Where k=i, m.

These solutions involve the decision for the quantities of goods and leisure consumed

(consumption demand side). Equations (5), (6) and (9) give us a complete picture of the

economic behavior of the farm households’. They are combined through the profit effect,

because income is determined by the households’ s' production activities, implying that changes

in variables influencing production also changes income, which in turn affects consumption

behavior. Incorporating the households’ characteristics that shape its preferences (Dh), the

demand for food indicated in Eq. (9) can be rewritten as

Fk = Fk [ Pi , Pm ,w , Y* (w , A0 ,K0 ,N ) ,Dh ] ---------------------------(10)

Where k=i, m.

3.4- Empirical model

Determining the demand for both home-produced and market-purchased goods, we can now

calculate the amount of calories (Ci) available in the respective food items. Then, the extent of

households’ food security is determined by the difference between caloric availabilities and

needs. Defining C* i=Ci−γi, where Ci is caloric availabilities and γi is the consumption needs for

the ith households’, C* i≥ 2100 kcal indicates that the households’ is food secure while C* i < 2100

kcal indicates that the households’ is food insecure, implying that the same independent variables

identified in Eq.(10) can be used in a food security model. Assuming a linear function, we can

write the food security equation as

43

Pi= F(Zi) =F(α + ∑ βiX i) = -------------------------------- (11)

Where e is the base of the natural logarithm, i represent the ith explanatory variables Pi is the

probability that an individual is being food insecure given X i, α and βi are regression parameters

to be estimated.

The dependent variable (food security) is measured using a proxy that the households’ observed

to be food secure (Zi= 1) is assumed to have C* i≥2100 kcal; while the households’ observed to

be food insecure (Zi= 0) is assumed to have C* i <2100 kcal. Since the dependent variable Zi is a

discrete variable, the food security model can thus be cast as a qualitative response model where

Pi is the probability of food security, which can be written as

Zi = ln( ) =α + β1X1 + β2X2 + -------βmXm-------------------------(12)

ln( ) = β0 +∑ βjX ij+ εi

here Pi is the conditional probability of food security; βj's are parameters to be estimated;

(X1)Family size, (X2) farm size, (X3) livestock owned(TLU), (X4) total off-farm income (X5)

education of households’ head,( X6) amount of food aid received,( X7) technological

adoption,(X8) access to infrastructure,( X9) participation in public meeting,( X10) extension

service adoption, (X11) land quality (land quality measured by farmers’ perception of the fertility

of their farmland),( X12) saving,( X13) number of month food purchased, (X14) age of

households’ head, (X15) sex of households’ head,( X16) access to irrigation are identified

potential variables that determines households’ food security problems in Kamba woreda.

3.5 Variables and working hypothesis

The number of variables that would be included in the model should deliver optimum possible

information. In this study the selection of the variable for the final logistic model was made by

44

looking the association between each predictor variables with the response variable. A minimum

of 10 events per independent variable has been recommended for sample size and dependent

variable efficiency (Hosemer-Lemeshow, 1989). The separate effect of each predictor variable in

explain the outcome variable was made by postulating the null hypothesis that H0: βi=0 against

the alternative H1: βi ≠ 0 for at least on i=1, 2, 3----n. The significance test for each coefficient in

the model was done using the Wald-chi-square ([β/s.e(β)]2 which is distributed as a chi-square

with degree of freedom) and likelihood ratio test. A likelihood ratio (LR) chi-square test was also

employed to examine the importance of each predictor variables to the outcome variable.

Therefore, the following sixteen independent variables wear selected to analyze the hypothesis

whether they explain a households food security status or not. Review of literature, working as

an expert in the agricultural office in the study area, degree of attention given by the government

policy, existence of chronic food security problem, unpublished local NGOs and local

government reports wear used as important sources to identify the potential determinants of

households’ food security in the study area. Some variables like access to irrigation, oxen

ownership, age of households’ head and sex of households’ head are more used in descriptive

rather than in logit model.

3.6 The dependent variable of the model (HFST): The households’ food security status is a

discrete variable representing the status of households’ food security. It was represented in the

models by two possible alternative ways: 1 for food secure and 0 for food insecure households’.

The information, which identifies the food secure from the food insecure, is obtained by

comparing the total food calorie available for consumption in the households’ per AE to the

minimum level of subsistence requirement per AE (2100 kcal). Households’ beyond this

threshold is said to be food secured, otherwise not.

3.7 Independent variables: households’ socio-economic characteristics such as households’

size, farm size, livestock ownership, total off-farm income, educational status of households’

head, food aid received, technology adoption, access to infrastructure, sex of households’ head,

age of households’ head, participation in public meeting, application of extension service,

45

saving, land quality and number of months food purchased are selected potential variables for the

logistic model and descriptive analysis.

Family size (FASZ):- Family size is measured by the number of family members in the households’.

As family size increases, obviously the number of mouths to feed from the available food

increases. Hence, it is hypothesized that family size and food security are negatively related. The

existence of large number of family members with limited resources could affect the food

security status of the households’. This is due to increasing demand for food with limited food

supply. Evidence in the literature indicates that larger family size have negative impact on food

security (Mulugeta Tefera, 2002; Abebaw Shimeles, 2003 and Ayalew Yimer, 2003).

Farm size (FRMS): Farm size is the total farmland owned by the households’ measured in hectares.

Losses of farm land to other uses because of population pressure and limits to the amount of

suitable new land that can be brought in to production is one of the constraints of food

production (Brown et al., 1990). Fertile farmland is often sacrificed to meet the growing

demands of population growth (Ehrlich et al., 1993). As the cultivated land size increases,

provided other associated production factors remain normal, the likelihood that the holder gets

more output is high. This variable represents the total cultivated land size of a households’ in

hectare. It was hypothesized that farmers who have larger cultivated land are more likely to be

food secure than those with smaller area.

Livestock holding (TLU): livestock holding refers to the total number of livestock holding of

the farmer measured in tropical livestock units (TLU). Livestock production constitutes a very

important component of agricultural economy, a contribution that goes beyond direct food

production to include multipurpose uses such as skins, fertilizer and fuel, as well as capital

accumulation. Furthermore, livestock are closely linked to the social and cultural life of farmers

for whom animal ownership ensures varying degrees of sustainable farming and economic

stability (Sansoucy, 1995). Therefore, it was expected that a higher possession of livestock

increase the probability to be food secure.

46

Access to infrastructure (INFRA ): Physical access to the infrastructure is measured by the amount of

Km required to reach the nearest local infrastructure. Nearness to infrastructure creates access to

additional income by providing access to increase productivity, easy access to inputs,

transportation and off-farm employment opportunities. The shortest distance to the infrastructure

was used in this study to determine how often the farmers used the infrastructure to sell and

purchase their produce. It was, therefore, expected that households’ nearer to infrastructure have

better chance to improve households’ food security status than who do not have proximity to

infrastructure centers. Proximity to infrastructure centers was measured in kilometer. Mulugeta

Tefera (2002) reported that market distance has no significant effect on food security. In this

study market distance was the main focus relative to other infrastructures.

Age of the households’ head: Age matters in any occupation. Rural households’ mostly devote

their lifetime or base their livelihoods on agriculture. It was argued as the age of the households’

head increases the farmer acquires more knowledge and experiences with possible negative

impact on food insecurity. In other ways, it was expected that younger farmers are more likely to

be food insecure than the older farmers that the older ones due to better possession of resources

accumulation. In light of this, it is hypothesized that ages of the households’ heads and food

security are positively correlated.

Irrigation: In areas like in Kamba where agriculture is the prime source of livelihood of the

society, soil moisture is very crucial. Even if the climatic condition in a given area is conducive,

then it would be far better to be supplemented with irrigation so that increased output could be

attained. However, in the study area drought, erratic rainfall patterns and other factors limit the

output per hectare, and made it one of the food insecure districts in the region. Hence, it was

hypothesized that the use of irrigation and food security are positively related

Sex of households’ head (SEX): women farmer may need a long adjustment period to diversify

their income sources fully and become food secure (Christina et al., 2001). Labor factor plays a

great roll in the study area. With regard to farming experience and access to technology, males

are better than female farmers. So sex of the households’ head is an important determinant of

47

food security. Therefore, it was hypothesized that male-headed households’ are more likely to be

food secure.

Off-farm income (TOFFI): When crop production and income earned from sales of livestock

and livestock products become inadequate to subsist the farming households’ of the study area

they often depend on external or other source of income to purchase food and farm inputs. So

income earned from off farm activities is an important variable, which determines households’

food security in the study area. Having multiple livelihood strategies increase chance to be food

secure for rural people like in Kamba. Hence, it was expected that the availability of off-farm

income is positively associated with households’ food security status.

Education (EDUC): Education equips individuals with the necessary knowledge of how to

make a living. Literate individuals are eager to get information and use it. Hence, it is supposed

that households’ who have had at least primary education or informal education are the ones to

be more likely to benefit from agricultural technologies and thus become food secure.

Total food aid (FAID ): food aid is given as a copping strategy to food insecurity in the study

area. Food aid can develop a dependency behavior among households’ which in turn will reduce

farmers’ motivation towards food self sufficiency. Therefore, food aid was expected to have a

negative relation to food security. The amount of food aid given was measured in kg. According

to Mulugeta Tefera (2002); Abebaw Shimeles (2003) and Ayalew Yimer (2003) food aid has no

significant effect on food security.

Technological adoption (TEC): Technological adoption determines the households’ food

security, those households who used improved seed, chemical fertilizer, apply proper agricultural

practices increase productivity and increase chance to become food secure.

Participation in public meeting (PAPUM):- households who participate in public meeting

have enough information about current input and output price, in put availability, credit access,

technology adoption and have higher chance to increase production than non-participants.

Therefore, public meeting was expected to have a positive relation to food security.

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Extension service (EXTN):-It refers to the number of days per year a farmer was visited by a

development agent for technical guidance has influence on both productivity and food security.

The higher the linkage between farmers and development agents, the more the information flows

and the technological (knowledge) transfer from the latter to the former. Those farmers who have

frequent contacts with development agents are likely to produce better than others and would be

in a better position of food security status.

Saving (SAVG) - Saving in the study area is in the form of either grain storing or purchasing

animals. Hence, saving in the form of animal purchase and grain storing has several advantages

in that source of income from the sale of their product; income from the sale of animal fatting

and above all it serves as a hedge at time of crop failure (drought). Generally, it is assumed that

households’ who have saving experience would have better food status than less saved.

Land quality (LNDQ):- Land quality measures farmers’ perception of the fertility of their

farmland. Households’ were asked to indicate whether they consider their land as fertile and not

fertile. Under optimal management, better land quality boosts crop production (Sah, 2002).

Stephen (2000) found that a decline in soil fertility negatively affects food security. It is expected

that this study was expected land quality affects food security status of households’ positively.

This is because the increase in the fertility of the land is expected to contribute positively

towards increase in crop output and consequently increase in farm income and food security.

Number of month’s food purchased (NMFP):- As the number of month’s food purchased

increase the probability to be food secured decreased. Subsistence farmers like in Kamba

produce food for home consumption. Farmers buy stable foods when their production does not

meet food demand. Numbers of months that farmers buy food items indicate the level of food

security. It has inverse relationship with food security statues of households’.

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Table 3:- Types, codes and definition of variables to be used logit model

Variable Variable type Variable definition

FASZ Continuous Family size in number

AIR Continuous Access to irrigation in hectare

FRMS Continuous Cultivated land size in hectare

TLU Continuous Total livestock holding in TLU

TOFFI Continuous Total off farm income earned in birr(2010/11)

EDUC Continuous Total grade of education

FAID Continuous Food aid obtained in Kg (2010/11)

TEC Dummy 1, if the households’ head used inputs 0, if the households’ head does not used inputs.

INFRA Continuous Access to infrastructure in Km

PAPUM Dummy 1, if the households’ head participate in public meeting, 0 if the households’ head does not participate in public meeting.

EXTNS Dummy 1, if the households’ head got extension service, 0 if the households’ head does not got extension service.

SAVG Continuous Amount of birr saved (2010/11)

NUMFP Continuous Number of months food item purchased

3.8 Interpretation of the coefficients of the logistic regression model The estimated coefficients for the predictor variables in logistic regression represent the slop or

rate of change of a function of the outcome variable per unit of change in the predictor variables

(Hosemer-Lemeshow, 1989).Thus, interpretation involves two issues:- i) determining the

functional relationship between the outcome variable and the predictor variable. ii) Appropriately

defining the unit of change for the predictor variable (Hosemer-Lemeshow, 1989).

50

The estimated logistic coefficients βi's reflecting linear and non- linear relationships and they are

interpreted as the change in the- log-odds for every unit increase/decrease (depending on the

variable change in X i) holding other variables constant.

Odds, odds-ratio and the marginal effects are all important basic terms in logistic regression

parameter estimates (β coefficients) of explanatory variables used in logistic regression equation

to estimate the log-odds that dependant equals 1(binomial logistic regression).Odds ratio is the

ratio of the probability that something is true or happen divided by the probability that something

will not happen. Odds ratio above one refers to the odds that the dependent variable equals one in

binary logistic regression. The closer the odds ratio to unit, the more the predictor variables

categories are independent of the outcome variable, with 1 representing full statistically

independency.

3.9 Marginal effects result in logistic model

Marginal effect, which is one of the results of logistic regression, shows us what the effect of a

change a given predictor on the output response variable would be at the sampled mean values

for the continuous variables and when the value of dummy variables changes from zero to one.

The marginal effect, in binary regression model, is the slop of probability curve relating Xi to Pr

(Y i=1/Xi), holding all other variables constant. It measures the change in probability of

occurrence for a unit change in Xi's at their mean value. The positive sign of marginal effect

indicates that the probability of households’ to be food secure will be increased at the mean value

of continuous predictors while the negative sign indicates that the probability of households’to

be food secure will decline at their respective mean. The marginal effect of the discrete variable

indicates that the likelihood of households’ probability to be food secure will increase as the

value changes from zero to one

3.10 Testing Multicollinearity

Multicollinearity in logistic regression is a result of strong correlations between independent

variable. Maddala (1989) described that high inter-correlation among the predictor variables by

themselves need not necessarily cause any problems in conclusion. Whether or not this is a

problem will depend on the magnitude of the error variance and the variance of the predictor

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variables. Multicollinearity may be induced due to poor sampling method, miss measurement

and over fitting of a model as well as improper use of dummy variables. There are a lot of

statistically accepted thumb rules that have been proposed for detecting multicollinearity among

categorical predictor variables. For this study variance inflation factor (VIF) was used to detect

the existence of multicollinearity. The larger the value of VIF, the more 'troublesome' or

collinear the variable Xi . As a rule of thumb, if the VIF of a variable is greater than ten then the

variable is said to be highly collinear (Gujarati 4th edition).

3.11 Measuring intensity of Food security (FGT)

With the increased awareness and availability of data, various measures of poverty have been

developed overtime, among which the Foster, Greer And Thorbecke (FGT) class of poverty

index is the most commonly applied (Ayalneh 2002). This index was initially suggested by

Foster, Greer and Thorebecke (1984) and has several desirable properties that have enhanced

recently by IFPRI for the purpose of food-insecurity analysis (Hoddinott, 2002). Therefore, this

study employs the FGT index in order to estimate the food security gap and its severity among

the rural households’. The FGT index can be specified as follows:-

F (α) = [ ] α---------------------------------------- (13)

Where n is the number of sample households’ s; yi is the measure of per adult equivalent food

calorie intake of the ith households’ ; m represents the cutoff between food security and

insecurity (expressed here in terms of caloric requirements); q is the number of food-insecure

households’ s; and α is the weight attached to the severity of food insecurity. In the above

equation if m-yi = 0 if yi > m. Hoddinott (2001) further explained that giving no weight to the

severity of food-insecurity is equivalent to assuming that α = 0. So then, the formula collapses to

F (0) = , this is called the head count ratio.

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CHAPTER FOUR

RESULTS AND DISCUSSION

This chapter presents the study findings in two categories as a descriptive and econometric

model analysis of the survey data. Descriptive statistics such as mean, standard deviation,

percentage, maximum and minimum were employed and binary logistic, econometric model was

used to identify determinants of food security at households’ level in the study area. Dimensions

of households’ food security, in terms of extent and severity, were computed by using an FGT

(Foster, Greere and Thorbecke) index.

4.1 Measuring food security status of households

Based on the methodology described in the previous chapter the following alternative results

were found: The information to categorize households’ s into food secure and insecure groups

was obtained by comparing the total households food or calorie acquisition per AE per day to

the minimum level of consumption required to ensure survival per AE per day. Thus those

households’ who have energy per AE beyond the minimum subsistence requirement (2100kcal)

are deemed to be food secure, otherwise food insecure.

Considering 2100kcal as a benchmark, only 79 sample households’(39.5%) were found to be

able to meet the minimum subsistence requirement and 121 households (60.5%) were found to

be unable to meet their minimum subsistence requirement. Based on the Core Food Security

Module analysis, households’ were found to be grouped into four categories; food secure (above

2100Kcal) (39.5 %), mildly food insecure (1800Kcal-2100Kcal) (34.5 %), moderately food

insecure (1500Kcal-1800Kcal) (16.5 %) and severely food insecure (less than 1500Kcal) (9.5 %)

(Table3). Majority of the respondents were mildly food insecure followed by moderately food

insecure. This empirical assessment results can serve as an instrument to guide decision as to

which status should be given more emphasis to reduce the problem.

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Table 4:-Food security status of sample households

Level of food insecurity Amount of calories Amount of HH in that interval Percentage

Food secure Above 2100Kcal 79 39.5%

Mildly food insecure 1800Kcal-2100Kcal 69 34.5%

Moderately food insecure 1500Kcal-1800Kcal 33 16.5%

Severely food insecure Less than 1500Kcal 19 9.5%

Total 200 100%

Source: - Survey data (2011)

4.2 Demographic and socio-economic characteristics

Socio - economic characteristics of sample households’ by family size, sex and education level

are summarized in relation to the food security status at households’ level. Possible explanations

on factors believed to have contribution to households’ food security are also presented from

analysis of descriptive output.

Family size

Family size was considered and hypothesized as one of the potential variables that would have

due contribution for food security. The proportion of sample households’ becoming food secure

decreased as the family size increases. About 46 percent of the 36 food secure and 23 percent of

the 28 food insecure sample households’ were found to have family size less than or equal to 5.

The number of food secure households with family size six and above is less than insecure

households which constituted 54 percent and 77 percent of the food secure and food insecure

households, respectively.

The survey result also revealed that there was significant difference in the mean family size at

less than 1 percent probability level (p<0.01) between food secure and food insecure sample

households’. In that, the mean was found to be 4.32 and 7.04 for food secure and food insecure

households’ respectively. While the overall mean family size of the sample households’ was

5.97. This was above the national average of 5 persons (CSA, 1994). This result is in agreement

54

with the prior expectation. The largest family size of the sample households’was 12 and the

smallest was 2 (Table 4).

Table 5:-Distribution of sample households’ by family size in number

Family size Food insecure Food secure Total

N=121 Percent N=79 percent N=200 percent

≤ 5 28 23% 36 46% 64 32%

≥ 6 93 77% 43 54% 136 68%

Total 121 100% 79 100% 200 100%

Mean 7.04 4.32 5.97

SD 0.17 0.13 0.15

Maximum 12 9 12

Minimum 2 2 2

t-value 12.72 Pr(T > t) = 0.0000***

Source: - Survey data (2011) *** Significant at less than 1% probability level

Households’ food security status and headship

Sex of households’ head was hypothesized to be one of the variables that make a difference on

the level of food security. Female headed households’ accounted for about 9 percent of the

sample households’. The survey result indicated that 8.3 percent of food insecure households’

were female headed whereas, the corresponding figure for male headed households’ was 91.7

percent. Male headed households’ comprise 89.9 percent of food secure and the remaining 10.1

percent food secure are female headed households’. The survey result showed no significant

difference (p > 0.10) on food security status of households’ in terms of households’ head sex.

The survey result showed insignificant which shows sex and food security status are unrelated

(Table 6).The possible reasons may be the female headed households coudn't face any labour

shortage problem due to capability of thire son for farming activeties.

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Table 6:- households’ food security by sex

households’

head

Food insecure(N=121) Food secure(N=79) Total (N=200)

χ2 NO percent NO percent NO percent

Male 111 91.7% 71 89.9% 182 91%

0.2024 Female 10 8.3% 8 10.1% 18 9%

Total 121 100% 79 100% 200 100%

Source: –Survey result (2011)

Households’ food security and education of households’ head

Most households’ heads in the survey were found to be Illiterate (55.5%) followed by junior

level education (23.5%) and primary (17.5%). There was specific pattern that indicated the

higher the level of education of the households’ head, the more food secure a households’ will

be. It was revealed that households’ headed by illiterate persons were more vulnerable to food

insecurity followed by primary. In societies such as Ethiopia where households’ heads are the

major breadwinners of the households’, households’ head’s educational status could determine

food security status of the entire households’. Among other things, households’ heads play a

pivotal role in shaping family members towards educational attainment thus reducing the

probability of being food insecure.

It was hypothesized that households’ food security and education of households’ head has

positive relationship. The survey result showed significant relationship at 5 percent probability

level when households’ educational level was categorized in to illiterate, write and read, primary,

secondary etc and became significant while categorized as literate and illiterate at less than 5

percent. Categorization of households’ head as literate and illiterate exhibited that 44.5 percent

of households’ heads were literate. Among the literate households 59 percent were found to be

food secure and out of 111 illiterate households 64.5 percent were food insecure (Table 7).The

possible implication is that in addition to other factors, while some level of education is

important to households’ food security

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Table 7:- households’ food security by educational status.

Level of education

Food insecure Food secure Total

χ2 N=121 percent N=79 percent N=200 percent

Illiterate 78 64.5% 33 41.8% 111 55.5%

9.96

1-4 25 20.7% 10 12.7% 35 17.5%

5-8 15 12.4% 32 40.5% 47 23.5%

Above 8 3 2.4% 4 5% 7 3.5%

Pr = 0.002*** Total 121 100% 79 100% 200 100%

Source:-Survey result (2011) *** Significant at less than 1% probability level

Number of month’s food item purchased

With respect to the specific characteristics of food secure and food insecure households’

number of month’s food item purchased was hypothesized to be negatively or inversely related

with food security. So, households’ with small number of month’s food item purchased tend to

be food secure than those with large number of month’s food item purchased. Accordingly, the

statistical analysis showed that number of month’s food item purchased is significantly different

for the two groups at one percent probability level. The mean number of month’s food item

purchased for food insecure households’ is about 4 months while that of food secure average

number of month’s food purchased is almost 1.5 months. Almost half of the sample households’

fill the food demand gap by purchasing food items for three to four months (Table 8). The

possible reasons for purchase is due to existence of inadequate own production.

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Table 8:- Distribution of sample households’ by number of month’s food item purchased

Number of months food purchased

Food insecure Food secure Total

N=121 percent N=79 percent N=200 percent

Does not purchase - - 25 31.5% 25 16.5%

1--2 25 20.6% 36 45.5% 61 23.5%

3--4 41 33.9% 14 18% 55 49.5%

Above four 55 45.5% 4 5% 59 10.5%

Total 121 100% 79 100% 200 100%

Mean 3.7 1.5 2.87

SD 1.15 1.13 1.57

Maximum 7 5 7

Minimum 1 0 0

t-value -0.0104 Pr(T > t) = 0.0000***

Source:-Survey result (2011) *** Significant at less than 1% probability level

Age of households’ head: - The mean age of sample households’ heads was found to be 46.13

with standard deviation of 11.53. The statistical analysis revealed that there was no significant

difference in the mean age of the households’ head between food secured and food insecure

households’ heads at 5 percent probability level of significance. This finding was turned out to

be opposite to the prior expectation, which argued as the age of the households’ head increases

since he can acquire more knowledge and experience he would be more prone to be food secure.

58

Table 9:- Distribution of sample households’ heads by age

households’

head age

Food insecure Food secure Total

N=121 percent N=79 percent N=200 percent

< 35 13 11% 10 13% 23 11.5%

35-46 60 50% 39 49% 99 49.5%

47-59 26 21% 14 18% 40 20%

≥ 60 22 18% 16 20% 38 19%

Total 121 100% 79 100% 200 100%

Mean 46.32 45.83 46.13

SD 11.25 12.00 11.53

Maximum 80 75 80

Minimum 24 28 24

t-value 0.28 Pr(T > t) = 0.3871

Source:-Survey result (2011) Land holding per households’ and per capita From any other productive resources land is by far the most important resource in agriculture.

The fertility status, location and other attributes of land in association with its size made it a

binding resource in agriculture. In the study area, as witnessed by the survey result there is

significant difference in the mean cultivated land size between the food secure and food insecure

households’. The mean farm size of food secure and food insecure households’ was found to be

1.19 ha and 0.91 ha, respectively. The overall mean farm size was 1.01 ha. As indicated in the

table below, about 4 percent and 29 percent of the total food secure and food insecure

households’ groups had farm size less than 0.47ha. But, percentage of sample households’ in the

other extreme holding brackets differs sensibly. For instance, 71 percent of the food insecure and

96% of the food secure had farm size greater than 0.47 hectare. Similarly, it was the largest

proportion of sample households’ (81%) had farm size greater than 0.47 hectare.

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Table 10: - Distribution of sample households’ by farm size per households’ (in hectare)

Farm size/HH

Food insecure Food secure Total

N=121 percent N=79 percent N=200 percent

< 0.47 35 29% 3 4% 38 19%

≥ 0.47 86 71% 76 96% 162 81%

Total 121 100% 79 100% 200 100%

Mean 0.91 1.19 1.01

SD 0.60 0.58 0.61

Maximum 3 3.5 3.5

Minimum 0.125 0.5 0.125

t-value -3.38 Pr(|T| > |t|) = 0.0009 ***

Source:-Survey result (2011) *** Significant at less than 1% probability level

Livestock holding

Livestock production plays an important role both in the crop producing and pastoral areas of the

study area. Livestock provide milk, meat, manure, traction power and transport. Livestock that

are owned by the sample households’ include cattle, sheep and goat, equine and poultry. The

total livestock population owned by the sample respondents was 742.558 in TLU. The percent

share of goat and sheep is larger than any of the other types of livestock among the sample

households’. This signifies the importance of small ruminant production in the study area, both

as a store of wealth and as check or control of food shortage during time of stress. Almost all

households’ in the sample own livestock with different combination. Survey result demonstrated

that the average numbers of livestock holding between the two groups of sample farmers differ.

In order to make comparison of the animal size between the farmer groups, the herd size was

converted into livestock units (TLU) based on Storck et al. (1991) (see Appendix 1).Food secure

group own averagely relatively larger number of livestock’s 6.6 in TLU and the food insecure

households owns averagely 2.9 TLU only. Almost more than half (54%) sample households’

own less than 3.94 TLU and 46% sample households’ own greater than 3.94 TLU. The

categories of livestock size indicate the wealth status of the households’ and the variation in this

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aspect may indicate variation in vulnerability of the households’ to food security problem. The

mean difference between the two groups is statistically significant at less than one percent level

of significance.

Table 11:- Distribution of sample households’ by Livestock Holding by TLU

Livestock holding in TLU Food insecure Food secure Total

N=121 percent N=79 percent N=200 percent

< 3.94 75 62% 33 42% 108 54%

≥ 3.94 46 38% 46 58% 92 46%

Total 121 100% 79 100% 200 100%

Mean 2.9 6.6 4.4

SD 1.5 1.7 2.4

Maximum 11.6 14.3 14.3

Minimum 0.13 0.13 0.13

t-value -15.3 Pr(|T| > |t|) = 0.0000***

Source:-Survey result (2011) *** Significant at less than 1% probability level

Ox ownership

Livestock is an integral part of crop production activities in the study area. It provides substantial

non-human labor and manure to the soil. With regard to the contribution of labor, oxen

ownership is an important variable. In the study area, as witnessed by the survey result only

twenty households’ owns more than 2 oxen (10%). Otherwise the households’ are ox-less or own

only one or two. As it is shown in the table below, above 31 percent of sample households’are

ox-less and owns only one ox and only 28 percent of the sample owns two oxen. Moreover, the

result revealed that there is significant difference between the two groups with regard to ox

ownership. This high variability between the two groups is correlated with the cost of

maintaining an ox and some households’ use farm tools for their farm operation in the study

area.

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Table 12:- Distribution of sample households’ by oxen

Number of oxen Food insecure Food secure Total

N=121 percent N=79 percent N=200 percent

No oxen 41 36.4% 21 26.6% 62 31%

1 44 36.6% 18 22.8% 62 31%

2 28 23% 24 30.4% 52 28%

≥ 2 4 4% 16 20.2% 20 10%

Total 121 100% 79 100% 200 100%

Mean 0.81 1.32 1.01

SD 0.86 1.01 0.95

Maximum 4 4 4

Minimum 0 0 0

t-value -3.68 Pr(T > t) = 0.0003***

Source:-Survey result (2011) *** Significant at less than 1% probability level

Relief food aid

Food to the households’ is acquired either from own production or through purchase. When

households’ exhaust their own produce, they attempt to entitle themselves to the food they want

through purchase. However, households’ mostly fail to do so due to the fact that income from

other sources is not sustainable and hence they depend on relief food aid. The study area is

known with its sequential food aid receive. Food aid plays a role to lessen the households’ from

being vulnerable to sever food insecurity. In this study it was hypothesized that households’ who

received more aid will be more likely to escape from being vulnerable to food insecurity than

those who received less. However, the mean amount of food aid received by the two sample

households’ groups revealed no significant difference (Table 13). The statistical insignificant

difference with respect to the mean amount of food aid received between the food secure and

food insecure households’ groups is possibly because of the targeting problem. That is, the food

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aid is distributed without discriminating the two groups and some times for all with no

participation in EGS program.

Table 13:- Distribution of households’ by amount of food aid received in Kg

Food aid received in Kg Food insecure Food secure Total

N=121 percent N=79 percent N=200 percent

Received no food aid 65 54% 45 57% 110 55%

Received less than 75Kg 22 18% 18 23% 40 20%

Received greater than 75Kg 34 28% 16 20% 50 25%

Total 121 100% 79 100% 200 100%

Mean 46.86 38.10 43.4

SD 63.57 54.17 60.05

Maximum 375 270 375

Minimum 0 0 0

t-value 1.01 Pr(T > t) = 0.1572

Source:-Survey result (2011) Use of technology

The table below shows the distribution of sample households’ by status of use of agricultural

technologies. In the survey it was observed that 45.5% of the overall sample households’ are

users of fertilizer and improved seed. To compare the two sample groups 22% of the food

insecure households’ were users of fertilizer and improved seed. While the corresponding food

secured households’ who were users of fertilizer and improved seed were 81%. Though such

difference was observed between the groups, it was statistically significant. The result also

showed that there is significant relationship between food secure and food insecure at less than

1percent.

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Table 14:- Distribution of sample households’ by status of use of technology Agricultural in put Food insecure Food secure Total Pearson chi2(1) χ2

N=121 percent N=79 percent N=200 percent

Use in put 27 22% 64 81% 91 45.5% χ2= 85.1464

Does not use in put 94 78% 15 19% 109 50.5%

Total 121 100% 79 100% 200 100% Pr = 0.000***

Source:-Survey result (2011) *** Significant at less than 1% probability level

Off-farm income

households in the study area perform various off farm activities like livestock trading, grain

trading, wage employment, timber production, hand craft and vegetable trading etc. The income

from such activities greatly improves the households’ purchasing power in the study area

especially during time of stress. Some of the people in the study sample had no access to off-

farm work. From 200 households’ sampled, 104 households’ heads had off-farm employment

while the rest of the households’ did not. 49 percent of those who had off-farm employment were

food secure while 53% were food insecure households. Table 15 shows the distribution of

households by income from off-farm activity. The survey result revealed that about 48 percent of

the sample households’ earn less than Br. 500 from these sources in the study area. But when we

further look the results within the sample groups above 68 percent of the food insecure and

above 51 percent of the food secure households’ earn less than Br. 500 from off farm activity per

year. Moreover, the survey result also revealed that there is significant difference in the mean

annual income from off farm activity between the two sample groups at less than 1 percent

(p<0.01) level. This result is in a complete agreement with the prior expectation.

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Table 15:- Distribution of sample households’ by off-farm income in birr.

Off-farm income Food insecure Food secure Total

N=121 percent N=79 percent N=200 percent

≤ 500 83 68% 51 51% 134 48%

501---1000 22 18% 12 30% 34 36%

1001---2000 12 10% 13 15% 25 12.5%

Above 2000 4 3.5% 3 4% 7 3.5%

Total 121 100% 79 100% 200 100%

Mean 399 951 617.3

SD 813.7 676.17 807.3

Maximum 7000 3600 7000

Minimum 0 0 0

t-value -5.01 Pr(|T| > |t|) = 0.0000***

Source:-Survey result (2011) *** Significant at less than 1% probability level

Irrigation

Access to irrigation is expected to have a positive relationship with households’ food security

(Burton et al., 2005). Farmers with plots on the irrigation schemes are able to grow crops

throughout the year and meet households’ food requirements than those on dry land farming.

Based on the analysis only 12% of sample households wear access to irrigation and 88% of

sample households do not have access to irrigation and practice dry land and rain fed

agriculture. However, households’ that have irrigation farm size below one hectare were 7% for

food insecure and 15% for food secure. The table also shows that it is impracticable to be food

insecure holding irrigation farm size above one hectare. While the survey result also revealed

that, there is significant difference between the two groups at less than 1 percent (p<0.01) level.

This result is in a complete agreement with the prior expectation.

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Table 16:- Distribution of sample households’ by irrigation farm size in hectare Irrigation participation Food insecure Food secure Total

N=121 percent N=79 percent N=200 percent

No irrigation farm size 112 93% 64 81% 176 88%

0.5—1hectare 9 7% 12 15% 21 10.5%

Above 1hectare - - 3 4% 3 1.5%

Total 121 100% 79 100% 200 100%

Mean 0.74 0.18 0.12

SD 0.26 0.39 0.32

Maximum 1 2.25 2.25

Minimum 0 0 0

t-value -2.48 Pr(T < t) = 0.0069***

Source:-Survey result (2011) *** Significant at less than 1% probability level

Access to infrastructure Nearness to infrastructure creates access to additional income by providing access to increase

productivity, easy access to inputs, transportation and off-farm employment opportunities. The

shortest distance to the infrastructure was used in this study to determine how often the farmers

used the infrastructure to sell and purchase their produce. It was, therefore, expected that

households’ nearer to infrastructure have better chance to improve households’ food security

status than who do not have proximity to infrastructure centers. Table 17 depicts the statistical

results of the two groups in relation to the effect of infrastructure distance on food security. The

result was statistically insignificant at less than 5 percent probability level. Additionally, the

mean distance of food secure group is greater than the food insecure ones. This result is contrary

to the hypothesis stated for this study. The occurrence of this result may be due to the fact that

when farmers are nearer to the infrastructure they would be tempted to sell their products and

buy non food items. But if they were away from infrastructure centers they would be food secure

by consuming their own product.

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Table 17:- Distribution of sample households’ by infrastructure distance in Km

Market distance(Km)

Food insecure Food secure Total

N=121 percent N=79 percent N=200 percent

Less than 5Km 84 69% 52 66% 136 68%

5—10km 31 26% 23 29% 54 27%

11—15km 5 4% 1 1% 6 3%

Above 15km 1 1% 3 4% 4 2%

Total 121 100% 79 100% 200 100%

Mean 3.28 3.66 3.43

SD 3.5 4.44 3.89

Maximum 18 25 25

Minimum 0 0 0

t-value -0.67 Pr(T > t) = 0.7476

Source:-Survey result (2011)

4.3 Incidence of food security by households’ factors

Table 27 shows the way in which some households’ factors affect food security by comparing

the incidence of food security among households’ groups sharing similar characteristics. The

occurrence of food security among households with less than four members is found to be 1.5

times more than that of households with five to eight and 2.7 times more than that of households

with nine to twelve. This decrease incidence of food security with increase in family size

confirms the result of the logit output discussed in the last section. In that the two variables have

negative relationship. As hypothesized the incidence of food security also decreases as the

proportion of children and elders increase in the family. This is also shown in the Table 27where

incidence of food security in households with dependency ratio greater than 2 is found to be 1.4

times lower than that of households with dependency ration less than 1. Moreover, the head

count index is 1.7 times higher in literate households’ heads than that of illiterate ones. Hence,

the risk of incidence of food security decreases with education, i.e., to say when the households

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turned from illiterate to literate status the incidence for the household to become food secure

increased. With regard to gender of households’ head, female-headed households have lower

incidence of food security than male-headed ones, i.e., 10%female and 90% male, respectively.

Likewise prevalence of food security increase as farm size of the households’ increases.

Table 18:- Incidence of food security by sample households

Characteristics households’ grouping Food secure Total Food security incidence

Family size 1—4 14 23 60.9

5—8 56 137 40.9

9—12 9 40 22.5

Over all 79 200 39.5

Education Illiterate 33 111 29.7

Literate 46 89 51.7

Over all 12 200 39.5

Dependency ratio <1 21 65 32.3

1—2 46 109 42.2

> 2 12 26 46.2

Over all 79 200 39.5

Sex Male 71 182 39.01

Female 8 18 44.4

Over all 79 200 39.5

Land size < 0.5 3 62 20.9

0.5—1 40 75 40

1.1—2 31 55 56.4

Above 2 5 8 62.5

Over all 79 200 39.5

Source: - Survey result (2011)

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4.4 Extent of Food security Food insecurity gap and severity of food insecurity were the indexes employed to capture the

incidence and severity of food insecurity. In the study area the incidence of food security was

found to be 0.395. That means only 39.5 percent of the sample households’ can meet the energy

requirement recommended for subsistence. In other words, head count ratio of 0.395 for 200

sample households’ means 97 sample households’ are deemed food secure. The head count

index or incidence of food security is good indicator to assess food security but it does not take

into account the severity of the food security problem. Therefore, to address how far the food

insecure households’ are below the subsistence energy requirement level, food security gap was

calculated from the survey data. Accordingly, the food security gap index came out to be 0.73.

This means that if the council mobilizes resources that can cover or meet the 73 percent of the

daily calorie requirement for every food insecure households and distribute these resources to

bring each households up to the given daily calorie requirement level, then at least in theory

food insecurity will be eliminated. In other words, assuming that the sample households are

representative to the rural population of Kamba and according to Office of Agriculture, it was

estimated to be 26,258 farming households in Kamba woreda which wear on average equivalent

to 140,480 in AE. Hence, based on the recommended subsistence energy (2100 kcal per day per

person), the total resource required to bring all households’ at least to get the daily subsistence is

amounted to 295,008,000kcal per day. When this amount of calorie is converted to cereals,

assuming that cereals can produce an average of 3700 kcal per kg, it becomes 797 quintal of

cereals per day. This implies that an estimated 291,702quintal of cereals per year is required to

bring all households’ at least to get the daily subsistence energy in a year.

4.5 Summary of mean difference and households’ scores Table 18 and 19 below show summary statistics and households’ scores of sample households’

groups on the hypothesized continuous and discrete variables included in the descriptive

analysis. According to the survey result depicted in Table 18, food insecure and secure

households’ groups revealed significant difference with respect to some socio-economic

variables like family size (FASZ), total farm size (FARMS), livestock holding in (TLU), total

off-farm income (TOFFI), number of oxen households’ own (NOXEN), number of months food

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item purchased (NUMFP) and access to irrigation (ACCIRR) at probability level less than 1

percent. On the other hand, Table 19 shows categorical variables with the chi-square value which

shows the existence of significant relationship between food secure and food insecure sample

households’ include the sex of households’ head (SEX), strong relationships between food

security status and technology adoption statues of sample households’ (TEC) and existence of

relationship between food security status and educational status of the households’ head

(EDUC).

Table 19:- Summary Statistics of continuous variables included in the descriptive statistics

Variable Food insecure (121) Food secure (79) t- value

Mean SD Mean SD

FASZ 7.04 0.17 4.32 0.13 12.72 ***

AGE 46.32 11.25 45.83 12.00 0.28

NUMFP 3.7 1.15 1.5 1.13 -0.01***

FARMS 7.04 0.17 4.32 0.13 -3.38***

TLU 2.9 1.5 6.6 1.7 -15.3***

NOXEN 0.81 0.86 1.32 1.01 -3.68***

FAID 46.86 63.57 38.10 54.17 1.0

TOFFI 399 813.7 951 676.17 -5.01***

INFRA 3.28 3.5 3.66 4.44 -0.67

ACCIRR 0.74 0.26 0.18 0.39 -2.48***

Source:-Survey result (2011) ***, is significant at 1% probability level.

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Table 20:- summary statistics of discrete variables included in the descriptive statistics

Variable Score Food insecure (121) Food secure (79) Chi-square value

Number Percent Number Percent

SEX 1 111 91% 71 90%

0 10 9% 8 10% 0.2024

TEC 1 27 22% 64 81%

0 94 78% 15 19% 85.15***

EDUC 1 43 36% 33 42%

0 78 64% 46 58% 9.96***

Source-survey result (2011) ***, is significant at 1% probability level.

4.6 Analysis of determinants of food security

An econometric model, logistic regression, was employed to identify the determinants of

households’ food security. However, before fitting the logit model, it was important to check

whether serious problem of multicollinarity, heteroscedasticity and association existence among

and between the potential continuous and discrete explanatory variables of the model estimation,

respectively. For this purpose, variance inflation factor (VIF) and contingency coefficient were

used for the continuous and discrete variables, respectively. Value of VIF greater than or equal to

10 is an indicator for the existence of serious problem of multicollinearity. Table 20 presents the

value of VIF for each of the continuous variables. As it is shown in the Table, the VIF of all the

variables were found to be smaller than 10. Hence, the problem of multicollinarity was not

serious among the variables. As a result, all the hypothesized 9 continuous explanatory variables

were included in the model estimation. Heteroscedasticity problem (different variance) was also

diagnosed by using commonly used 'Robust' order in STATA-10.

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Table: - 21 VIF value of continuous variables

Variable R2 VIF

FASZ 0.503 1.42

FRMS 0.464 1.87

TLU 0.503 2.01

TOFFI 0.209 1.26

EDUC 0.144 1.17

FAID 0.091 1.10

INFRA 0.295 1.42

SAVG 0.213 1.27

NUMFP 0.222 1.29

Source: Own computation

Similarly contingency coefficient was calculated for the discrete variables. Contingency

coefficient value ranges between 0 and 1 and as a rule of thumb variable with contingency

coefficient less than 0.5 assumes weak association between the variable. Contingency

coefficients for technology adoption, participation in public meeting, land quality and extension

service adoption of households’ heads were found to be lower than 0.25. Since this figure shows

the absence of serious association (multicollinearity) between the variables, all the four discrete

variables were included in the model.

Table 22:- contingency coefficient for discrete variables

LNDQ EXTN PAPUM TECH

LNDQ 1.0000

EXTN -0.0759 1.000

PAPUM -0.1437 0.0857 1.000

TECH 0.0750 0.1514 0.2321 1.000

Source: - Own computation

The variable food security (FODS) was used as a dichotomous dependent variable, with an

expected mean value of 1, indicating the probability of being food secure, 0 otherwise.

Generally, there were 13 explanatory variables included in the model analysis. In order to

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identify the most important factors from the hypothesized potential variables to influence food

security, binary logit model was estimated from the survey data. For the purpose, STATA

Version 10 was employed. Codes, types and definitions of the variables; and the maximum

likelihood binary logit estimates are presented in Table 22 and Table 23below, respectively.

Table 23- The maximum likelihood estimates of the logit model

Variable Coefficient p-value Wald Marginal

Statistics Effect (dF/dx)

FASZ -5.442 0.000*** 26.13 -0.033

FRMS 9.91 0.000 *** 13.42 0.06

TLU 1.62 0.000 *** 19.01 0.01

TOFFI 0.00 0.002 *** 10.05 0.000

EDUC 0.5 0.049 ** 3.87 0.003

FAID 0.00 0.657 0.20 0.000

TEC 6.47 0.000 *** 13.54 0.0475

INFRA -0.07 0.087 2.94 -0.0005

PAPUM 7.18 0.000*** 14.54 0.100

EXTN 5.27 0.010 ** 6.57 0.011

SAVG 0.00 0.106 2.61 6.12

NUMFP 0.82 0.031** 4.64 0.005

LNDQ 8.32 0.000 *** 13.31 0.85

Constant -11.50 0.012

Wald chi-square 53.33***

-2Log likelihood 17.63

Likelihood ratio test 250.74

Sensitivity 94.94%

Specificity 97.52%

Percent correctly predicted (count R2) 96.50%

Sample size 200

*** Significant at less than 1% probability level

Source: Model output ** Significant at less than 5% probability level

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The likelihood ratio test statistics (250.74) exceeds the chi-square critical value (53.33) with 13

degree of freedom. The result is significant (p=0.000) at less than 1 percent probability level

indicating that the hypothesis that the coefficient except the intercept are equal to zero is

rejected. Another measure of goodness of fit used in logistic regression analysis is the count R2,

which indicates the number of sample observations correctly predicted by the model. The count

R2 is based on the principle that if the estimated probability of the event is less than 0.5, the

event will not occur and if it is greater than 0.5 the event will occur (Maddala, 1989).The H-

L(Hosmer-Lemeshow) test also revealed that the model has H-L value 1.00 which indicates

convergence between expected and observed probabilities, value is not statistically significant at

less than 5% probability level, therefore the model is quite a good fit, or indicating that the

model prediction does not significantly differ from the observed. In other words, the ith

observation is grouped as a food secure if the computed probability is greater than or equal to

0.5, and as a food insecure otherwise. The model results show the logistic regression model

correctly predicted 193 of 200, or 96.5 percent of the sample households’. The sensitivity

(correctly predicted food secure) and the specificity (correctly predicted food insecure) of the

logit model are 94.94 percent and 97.52 percent, respectively. Thus, the model predicts both

groups accurately.

4.5 Discussion on the significant explanatory variables

Out of the thirteen variables hypothesized to influence households’ food security, ten were found

to be statistically significant. The maximum likelihood estimates of the logistic regression model

showed that family size (FASZ), cultivated land size (FRMS), total livestock holding in (TLU),

total off farm income (TOFFI), educational status of the households’ head (EDUC),

technological adoption of households’ head (TEC), land quality (LNDQ), households’ head

participation in public meeting (PAPUM), extension service (EXTNS) and number of months

food purchased (NUMFP) were important determinants identified to influence households’ food

security in the study area. That means, the coefficient of family size, Cultivated land size, total

livestock holding, total off farm income, technological adoption of households’ head,

participation in public meeting and land quality were statistically significant at 1 percent

probability level of significance whereas educational status of the households’ head, extension

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service and number of months food purchased were statistically significant at less than 5 percent

probability level of significance. Moreover, the results verified that except number of month’s

food purchased, almost all of the explanatory variables obtained in the model had the signs that

confirm with the prior expectations. In light of the above summarized model results possible

explanation for each significant independent variable are given consecutively as follows:

Family size (FASZ):- This households’ factor is found to be highly significant to determine

households’ food security in the study area. Households’ size revealed a negative relationship

with food security and statistically significant at 1 percent probability level. The negative

relationship indicates that the probability of in favor of being food secure decreases with an

increase in the family size. This means that the probability of a households’ to be food security is

zero if households’ family sizes increase. The marginal effect of a unit change in family size,

computed at sample mean of family size, the probability of food secure is -0.033. This means

that the probability of food security decreased by -0.033(about -3.3%) for a one member increase

in family size. The likely explanation is that in an area where households’ depend on less

productive agricultural land, increasing households’ size results in increased demand for food.

This demand, however, cannot be matched with the existing food supply so ultimately end up

with food insecurity.

Cultivated land size (FRMS):- Cultivated land size was hypothesized to influence food security

positively. The results of the logit model indicated that sample households’ which had larger

farm size had more possibility of being food secure. This is assured by the positive coefficient of

this variable indicating it is significantly influencing rural households’ food security at 1 percent

level of probability. The possible justification is that farm households’ s which had larger farm

size had better chance to produce more, to diversify the crop they produce and also have got

larger volume of crop residues. The marginal effect of a unit change in farm size, computed at

sample mean of farm size holding in hectare, the probability of food secure is 0.06. This means

that the probability of food security increases by 0.06(about 6%) for a one hectare increase in

farm size. This result is supported by the findings of Abebaw Shimelese (2003).

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Total livestock holding (TLU):-The relationship between the amount of livestock holding in

tropical livestock unit and food security turned out to be positive and statistically significant. The

relationship is statistically significant at 1 percent probability level. This is an indication that

ownership of livestock acts as a hedge against food security in the study area. Livestock, besides

its direct contribution to subsistence need and nutritional requirement, is a vital input into crop

production by providing manure and serves to accumulate wealth that can be disposed during

times of need, especially when food stock in the households’ deteriorates. The marginal effect of

a unit change in livestock ownership in TLU, computed at average TLU owned by sample

households’, the probability of food secure is 0.01. This means that the probability of food

security increase by 0.01(about 1%) for a one unit increase in livestock number in TLU. This

result was also supported by Abebaw Shimelese (2003).

Total off-Farm Income (TOFFI): This variable represents the amount of income earned in cash

or in kind, during the year. In the areas like Kamba, where the farmers face crop failure and sales

of livestock and livestock product is inadequate, income earned from off-farm activities is an

important means of acquiring food. Accordingly, in the study area, the data revealed that 52%

households’ have off-farm income access and from food secured households’ 51% have access

to off-farm income and from food insecure 54% have access to the additional income. The result

suggests that households’ engaged in off-farm activities are endowed with additional income and

more likely to be food secure. Consistent with the hypothesis, off-farm income is positively and

significantly associated with farm households’ food security status (at probability level of 1 %).

The marginal effect of a unit change in amount of off- farm income in birr, computed at average

amount of off- farm income by sample households’ increases the probability of food security by

0.002%.

Education (EDUC):- Education is positively and significantly related to the probability of food

security in the study area. Education is also explained in terms of contribution to working

efficiency, competency, diversify income, adopting technologies and becoming visionary in

creating conducive environment to educate dependants with long term target to ensure better

living condition than illiterate ones. The possible reasons are literate farm households’ heads are

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more willing to adopt better production technologies, accept technical advice from extension

workers, and diversifying their source of income than the illiterate ones. As a result literacy

increases chance of becoming food security among the sample households’. The marginal effect

of a unit change in level of education, computed at average level of education by sample

households, increases the probability of food security by 0.002%.

Technological adoption of households’ head (TEC):- similar to expectation, use of chemical

fertilizer and improved seed was found to be positively and significantly affect the rural

households’ food security in the study area. Thus, the study reveals that most of the farmers who

applied chemical fertilizer and improved seed in their farm were more food secure than those

who did not apply chemical fertilizer and improved seed. The probable reason for this is that

application of chemical fertilizer and improved seed improves the mineral content of the soil and

restores the nutrients required by the crops, thus crop yields are increased. Input use by farmers

increases the probability of food security in the study area. Dry land farmers like in Kamba, who

are risk averse, can also be food secure from its use especially when the rains are adequate for

crop production. Keeping other factor constant, the marginal effect of change from technology

non user to technology user, computed at mean technology adoption status especially for

chemical fertilizer and improved seed by sampled households’ increases the probability of food

security by 5%.

Participate in public meeting (PAPUM):- The objectives of public meeting are to transmit the

governments plan and strategy to boost production. Participation in public meeting changes

farmers’ outlook towards production, by helping them to talk the main challenges faced, to

identify duty’s of government and local farmers and helps to get new arrival and trial

technologies. This may be also explained by the factors that the message that farmer gain from

public meeting help them to initiate to use risk aversion strategies that seek diversification of

income within and out of agriculture. This variable has a positive and significant (p<0.01)

association with the households’ food security. Keeping other factors constant; the odds ratio in

favor of food security, cetris paribus, and increases by a factor of 1317 as the households’ public

meeting participation trend changed from non- participant to participant in a year.

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Frequency of extension contact (EXTNS):- This households’ factor is found to be highly

significant to determine households’ food security in the study area. The objectives of extension

is to change farmers outlook towards their difficulties which assists them adapt better solution to

their livelihoods. Thus, the information obtained and the knowledge and skill gained from

extension office may influence farmers’ skill and decision making on seeking diversification.

The frequent extension contact received will increase the tendency of households’ to be food

security. Frequency of extension contact has a positive relationship with food security and

statistically significant at 5 percent probability level. The positive relationship indicates that the

odds ratio in favor of the probability of being food security increases with an increase in the

frequency of extension contact. Keeping other factors constant; the marginal effect of a change

from lacking contact to having contact to extension service provider, computed at mean number

of contact with extension service provider in a year by sample households’ s, increases the

probability of food security by 1.1%.

Land quality (LNDQ):- This is because the increase in the fertility of the land is expected to

contribute positively towards increase in crop output and consequently increase in farm income.

Empirical findings indicate that land fertility problem has a relation with the level of food

security. However, Mulugeta Tefera (2002) and Ayalew Yimer (2003) have shown that land

fertility problem do not have significant effect on households’ food security status. On the

contrary to their result, this study revealed that this variable affects households’ food security

significantly. The marginal effect of a change of farmers land from poor land quality to good

land quality, computed at mean farmers perception on the fertility of their farmland quality by

sampled households’ s, increases the probability of food security by 84.7%. This gigantic

response may be achieved after challenging and time consuming task of soil quality

improvement in long period of time. It is not an easy task and the response is not automatically,

it needs more time and actors commitment to get the above probability percent on food security.

Number of month’s food purchased (NMFP):- As the number of month’s food purchased

increase for rural farmers, the probability to be food secure decrease due to weak income source

stability which forces to purchase low quality food items. Subsistence farmers like in Kamba

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produce food for home consumption and buy food items when there is food shortage in the

family. If the number of months that a household’ buy food items is more, he has low own

production and depend on purchase for his food demand. Number of month’s food purchased has

inverse relationship with food security statues of households’. But the logit model revealed that it

has positive relationship with food security. The possible reason can be the farmer has chance to

buy diversified food items and goat higher calories than own production and frequent

consumption of the same food items. The marginal effect of a change from few numbers of

months for food purchase to most number of months for food purchase, computed at average

number of month’s food purchased by sample households’, increases the probability of food

security by 0.5%.

4.7 Major Agricultural Problems

Different reasons were given concerning the declining trend in production. The responses of

sample farmers on major reasons for the declining trend of crop production are shown in Table

25. Inadequate rain fall, soil infertility, small land holding, lack of credit, inadequate extension

service, poor technological diffusion and lack of oxen problems were ranked as a very serious

problems of farming households in the study area. Out of total respondents who cited the

various problems, about 60% of them mentioned inadequate rain fall, 45% mentioned soil

infertility, 41% mentioned small land holding and 39% mentioned lack of credit problem has

been very serious problems in the study area. Inadequate rainfall is the most frequently cited

agricultural problem. With regard to the proportion of farmers who respond on the major causes

of food insecurity problems (Table 25), relatively small numbers of the food secure farmers

reported to have these problems as compare to those food insecure groups. For instance, 38%

and 44% of food secure and food insecure farmers were cited absence of rainfall. In general, the

poor performance traditional farming practice that has greatly affected the sustainability of

production and productivity joined with the inadequate and erratic rainfall has made district’s

rural farm households’ more vulnerable and food insecure. The responses of sample farmers on

trend of food availability in the last five years revealed that 56% confirmed that food availability

was declined from year to year.

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Soil fertility problem is one of the physical factors affecting crop production. The relationship

between soil fertility problem and state of food security indicate that soil fertility problem has

negative impact on crop production performance, and causes a deterioration of food security

status of the households’. The proportion of farmers who reported to have soil fertility problem is

more for food insecure than secured groups. About 20% of food insecure and 17% of food secure

farmers reported to have soil fertility problem in their farm.

Table 24:- Major agricultural problems encountered in the study area

Source of problem Food insecure Food secure

N=121 Percent N=79 Percent

Inadequate rainfall 53 44% 30 38%

soil infertility 24 20% 13 17%

small land holding 18 15% 10 13%

lack of credit 10 8% 8 10%

inadequate extension service 6 5% 8 10%

poor technological diffusion 5 4% 6 7%

lack of oxen 5 4% 5 5%

Total 121 100% 79 100%

Source:-survey result

4.8 Extension services

In a country such as Ethiopia, where the majority of the farmers are illiterate, agricultural

extension plays a significant role in assisting them by identifying and analyzing their production

problems and by making them aware of opportunities for improvement of food security. Hence,

the effectiveness of the other inputs in production partly relies upon the availability of sound

agricultural extension services at community levels. The traditional and widely used means of

conveying new information to farmers is through the public extension services. In Ethiopia,

including the study area, development agents trained in agricultural sciences are assigned in each

kebele. The current agricultural policy gives emphasis to the development of private enterprise

including development of smallholders’ agriculture. The extension program requires farmers to

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use package of new varieties, chemical fertilizer, farm credit etc. However, only 39 % of the

sample farm households’ identified themselves to be beneficiaries of continuous extension

services the reaming 61% couldn’t get continuous extension service. The number of DA in the

woreda increased in number from 48 to 118 since 1994E.C, but the service promotion by them is

at infant stage. The percentage of food secure farmers with access to extension services is

relatively higher than the percentage of food insecure farmers. This could be because that food

secure farmers have more frequency of contact with the extension agents. Both the descriptive

and econometric results revealed that contact with development agent and application of

improved technologies were influential factors for food security in the study area.

4.9 Coping Strategies

Farm households’ in a vulnerable area like Kamba engage in several activities in order to avoid

food shortage and famine. These include adjustments farmers would make to cope with food

supply pattern, reduce amount of food consumed ,sale of livestock, labor (including migration) in

search for employment opportunities, sales of productive assets and stocks, depending on food

aid. Farmers were asked about how they manage food shortage and how they can cope with food

insecurity. This section describes the results of the interview and relates the response to the

farmers’ actual activities.

The local coping strategies, which have been practiced during food crisis by groups of sample

farmers in Kamba, are presented in Table 26. The principal strategies used by the sample

respondents to mitigate food supply shortage include purchasing of grain, diversification of crop

production into drought resistant crops such as cassava, 'enset', sorghum, sweet potato haricot

been and others during short and erratic rainy seasons to meet their subsistence needs. Almost all

(99%) respondents diversified their production by producing drought resistant crops. About 52%

of all respondents and 49% of food secure and 54% of food insecure households’ engaged in off-

farm jobs. Even though, there was limited access to off-farm work opportunity in the district,

resource poor family migrate(17%) either within woreda or outside woreda for wage earned in

kind or cash. Another important coping mechanism considered first by farmers was sale of

livestock. Livestock, besides their complimentary relationship with crop production, provide

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hedging against risk of food insecurity. As a result, when food produced is fully consumed and

or no cash reserve is available to purchase more of it, animal products and live animals are sold

as ways of getting access to cash income and to buy food for the households’. Accordingly,

about 74% of all households’, 68% of the food secures and 94% of the food insecure households’

were involved in the sales of animals (mostly small ruminants) to acquire food whenever there is

shortfall in food supply. Sales of animals were common for the two groups and these shows that

the farm households’ keep animals as principal assets to manage the shortage. This mechanism is

ranked as the first most important coping practice, followed by, reducing food consumed, and

involvement in off-farm and food aid. Sales of live animals to purchase food grains during

supply shortage have considerable effects on farmers' economy mainly because of sharp decline

in livestock prices due to excessive supply from all affected farmers. The proportion of food

secure and food insecure households’ who practiced purchasing grains/food items during food

supply shortage were 92% and 95%, respectively. Reduction of consumption in terms of both the

number of meals per day and amount of food per meal was identified as means of coping for the

largest proportion (40%) of the respondents, 25% of the food secure and 53% of the food

insecure sample households’ during short supply. About 23% of all cases, 7% of the food

secures and 30% of the food insecure households’ reported that they overcome food shortage

problems by receiving relief food freely from government and non-government organizations.

These and other less frequently mentioned and practiced coping strategies are shown in Table 26.

Table 25:- Coping strategies common in Kamba woreda

Type of coping Over all

(200)

Insecure

(121)

Secure

(79)

Rank

Reduced amount of food consumed 40% 63% 58% 2nd

Sale of livestock 74% 94% 73% 1st

Wage work and migration 52% 54% 34% 3rd

Sale of productive asset and jewelers 2% 85% 25% 5th

Food aid 23% 30% 7% 4th

Eating wild food(in pastoral kebele) 7.5% 85% 3rd

Source:-Survey result N.B percent does not sum up to 100, due to multiple response.

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The analyses of the coping mechanism of the sample farmers have shown that, coping

mechanisms have different patterns. All farmers were not equally vulnerable to drought or food

insecurity; they responded in different ways. Some households’ implement some coping

strategies after all other options have been pursued and exhausted. As the food crisis persist,

households are increasingly forced into a greater commitment of resources, just as the

households’ exhaust the strategies that are available in the early stages of food crisis, they begin

to arrange key productive assets such as draft oxen, milk cow and assets and jewelers.

Accordingly, among the sample households’ 2% of them sold key productive assets and jewelers

as coping mechanism for food insecurity. With respect to the period of severe food shortage that

the farm households’ s practice these coping mechanisms differ area to area, more than 87% of

the households in low land and mid- altitude in the study area encountered severe food shortages

during the months of April, June and July and highlands in September, October and November.

According to woreda agriculture office, farm households’ in the lowland ecological zone and

pastoral areas face severe food shortage more frequently than those in the highlands. Pastorals

in the study area begun to eat wild foods as vulnerability increasing, and they shift to the

consumption of the cheapest and less quality food items. In general, the proportion of

households’ with local coping strategies implies the extent to which most of the Kamba district's

farmers are vulnerable to seasonal shocks and how food security problem is serious. Hence,

factors like chronic poverty, rapid population growth, declining per capita food production, poor

marketing infrastructure, lack of off-farm job opportunities, small land holding and lack of credit

facilities aggravated food security problem and made households’ more vulnerable.

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CHAPTER SIX

SUMMARY AND RECOMMENDATION

6.1 Summary of findings

Food security problem is the most crucial and persistent problem facing millions of rural

households’ in Ethiopia. Even though the country has considerable agricultural potential, more

than half of its rural households’ are unable to feed themselves throughout the year and yet food

availability in the country is largely determined by domestic staple food production by

subsistence agriculture. Producing enough food and achieving food security can be made

possible through increased agricultural productivity, increased off-farm income and improving

the ability of rural households’ to smoothen and stabilize their income and purchasing power,

this problem remained as a top and major challenge than ever met by the Ethiopian government.

This study was conducted in Kamba woreda of Gamo Gofa zone, where food security problem is

becoming virtually a continuous concern of most households’. Food security problem is now a

crucial problem in Kamba woreda. Most of the farming households’ in the district have

difficulties to cope with the situation even during normal seasons. Drought stimulated food

security problem has been a recurrent phenomena on exacerbating the vulnerability of the

resource poor farming households’ in the district. This chapter provides the conclusions and

recommendations drawn from the data analyzed on how agricultural production could be

improved in enhancing small-scale farmers to meet households’ food security. The chapter looks

at the aims of the study that were stated in the introductory chapter (Chapter 1), so that

conclusions and recommendations can be drawn.

The study area is not an exception of the above facts. The adverse climate nature of the

environment coupled with poor soil fertility, high population growth, lack of sufficient moisture,

week technology adoption, lack of infrastructure and traditional way of cultivation pulled back

the productivity of agriculture and ultimately resulted in food security problem to many of the

rural households’. Aware of these problems, the study was carried out with major objective to

establish which determinants played a major role in addressing households’ food security

84

problem in Kamba woreda. Other factors were also put into account in trying to explain which

factors are significant in enhancing households’ food security and estimation of the food security

gap and severity of food security problem.

The socio-economic characteristics of both the food secure and insecure households’ and the

livelihood strategies of the rural households’ in the study area were also considered deeply. To

accomplish these objectives primary data on food consumption habit, demographic & socio-

economic characteristics, livestock and crop diversity, access to productive resources, access to

service and infrastructure, marketing and credit, technology adoption trend, farm and off-farm

income, coping mechanisms etc. were gathered, organized, analyzed and interpreted to come

with possible results at the households’ level from 13 randomly select sample PAs. The analysis

employed both descriptive statistics and econometric methods. Descriptive statistics were

employed to illustrate weather there was strong relationship between dependant and explanatory

variables and existence of mean difference between the two groups with respect to food security

status. Binary logistic model was specified and estimated to identify determinants of food

security in Kamba woreda. FGT index was used for the computation of incidence and severity of

food security problem among sample households’.

Based on the survey data, an attempt was made to describe the socio-economic characteristics of

the food secure and food insecure sample households’ groups, i.e., whether there exists mean

difference between the two groups with respect to the different socio-economic attributes.

Accordingly, the survey result revealed that there was significant difference with respect to mean

of family size both in number and adult equivalent, and in the mean of dependent individuals.

Large households have more people to feed as compared to small households thus, reducing the

calorie intake per households’ member decreasing the food security in those households. The

mean in each case is lower for the food secure households’ group and higher for food insecure

households’. On the other hand, farm size, amount of off-farm income received also

differentiated the two groups significantly in their mean values. In all the two cases, the mean

values were higher for the food secure households’ group. The total livestock owned (TLU) was

found to be significantly and positively related (1% probability level) to the probability of being

85

food secure. The number of livestock’s owned in TLU differentiated the two groups significantly

in their mean values. Moreover, with regard to education, percent of illiterate households’ was

higher for the food insecure households’ group than the food secure ones. And there was

systematic relationship between education and food security. The use of modern technology

(TEC) especially chemical fertilizer and improved seed has come out to be significant (1%

probability level) and positive influence on the food security status of the households’. The

positive sign is an indicator of existence of efficient relationship between technology adoption

and food security. Number of oxen owned (NOXEN) is significant and has a positive association

(at1% probability) in affecting households’ food security situation. This implies that the

existence of oxen differentiated the two groups significantly in their mean value affects the

households’ food security in such a way that households who owned oxen have better chance to

escape serious food insecurity than those who don’t owned. Both number of months food item

purchased and access to irrigation farm influence the households’ food security positively and

significantly.

Binary logit econometric model was estimated using the survey data to identify the determinants

of food security among the rural households’ in the study area. Accordingly, the estimated

coefficient revealed a varied impression. On the one hand, family size, farm size, livestock

owned in TLU, total off- farm income, education, technology adoption , adoption of extension

service, land quality and participation in public meeting showed theoretically consistent and

statistically significant effect while coefficient of number of months food purchased showed

theoretically inconsistent and statistically significant effect. On the other hand, amount of food

aid received, saving and access to infrastructure were not found to be statistically significant in

determining food security.

A closer look at the model result reveals that the variable family size influenced the households’

food security negatively and significantly. This means the probability for the households’

becoming food secure decreases as the households’ size increases.

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Educational status of the households’ head also exhibited positive and significant coefficient.

This means the variable is directly related with food security. Likewise, farm size and adoption

of technology were also other significant variables came out to be positively and significantly

related with food security. Total off-farm income, participation in public meeting, land quality

and adoption of extension contact were exhibited positive and significant at less than 5 percent.

Number of month’s food purchased on the other hand, as opposite to prior expectation and has

a positive and significant coefficient in the estimated model result. This means those farmers

who buy food items from market for longer months may have chance to get diversified amount

of calories and increased chance of food security.

The other important variable is livestock holding. This variable in agreement with the prior

expectation came out to be positively and significantly related with food security. This is so due

to the fact that livestock both directly and indirectly contributes to the households’ food, energy

and income requirement. The head count ratio revealed that only 39.5 percent of sampled

households’ are found to be food secure and 60.5 percent of sample households’ are food

insecure. The gap and severity of food insecurity were estimated to be 73 and 3.95 percent

respectively. Considering the daily recommended 2100 kcal per adult equivalent, a resource

needed to bring all sample households’ to daily subsistence requirement amounted to 2,248,617

kcal. This shows daily requirements estimate of 607.7 quintals of cereal per day which is

equivalent to 221,823 quintals per year.

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6.2 Recommendations

Hence, after summarizing the findings of this study, the possible policy recommendations that can be made from this study are as follows:

1. Family size and food security are strongly and negatively related. Large households’

size exerts pressure on consumption than the labour it contributes to production.

Rural family size, like in Kamba have high youth dependency ratios(46.1%,CSA

2007) and low life expectancies, it imposes a substantial pull on areas economies by

reducing their productive capacity per capita associated with lower rate of savings

and investments (as conventionally measured), and therefore slower economic growth

and affects directly food security. Recent studies have shown that East Asia’s rapid

demographic transition in the past half century added markedly to the increase in

GNP per capita, especially in comparison with regions such as sub-saran Africa

where the demographic transition has been delayed (Barry Riley 2002). Relatively

poor food productivity and poor public health has probably slowed the demographic

transition in the Africa countries. Serious attention has to be given to limit the

increasing population in the study area. This can be achieved by creating sufficient

awareness to successful family planning through effective extension services and

integrated development strategy in the rural households’. So family size control is the

crucial concern in the rural area like in Kamba otherwise, the ever-shrinking

productive resources in the study area coupled with increasing population would

hamper any development intervention from achieving its objectives.

2. Productive resources especially land is very limiting and highly binding resource in

the study area. The model and descriptive analysis result showed cultivated land size

and soil fertility problem was found to be significant and they are positively and

negatively related with food security. An increase in land size is likely to increase

food security without employing any advanced technologies. Tackling the problem of

food security through increasing farm size would not bring any sustainable

improvement. So a medium and longer-term food security strategy through increased

food production must be introduced. In a medium or shorter term, distribution and

88

allocation of cultivable land, which was not under cultivation, thereby increasing

output, should be made. This would give short period relief from the problem;

otherwise the amount of return from such a strategy would not be by any means

sufficient and sustainable to up-root the problem from the present setting. As a result,

strong effort should be made to improve the production and productivity in the

agricultural sector in the longer term. The possible measures that can be undertaken to

achieve this strategy include, with the limited resources that the farmers have, it could

be rational to cultivate smaller pieces of land as in the case of the agricultural

production theory (Stage II of the production curve) by applying appropriate

conservation measures to improve soil quality and get better turn out.

3. The effect of education on households’ food security confirms the significant role of

the variable in consideration for betterment of living condition. Farmer’s education

helps for improving production and productivity of agriculture. The more households’

head educated, the higher will be the probability of educating family member and

familiar with modern technology, which the twenty first century so badly demands. In

order to bring food security at the households’ level the development strategy need to

encompass education programmes to the smallholders. So, strengthening both formal

and informal education and farmers training centers should be promoted to increase

food security in Kamba woreda.

4. The research findings showed that livestock ownership has positive impact on

households’ food security. Livestock sub sector plays a great role in the struggle to

eliminate food security problem. Its contribution to the households’ food energy

requirement and total income is significant. In the study area animal disease,

existence of local and low productive livestock’s and marketing conditions are very

crucial. Hence, necessary effort should be made to improve the production and

productivity of the sector. This can be done through the provision of adequate

veterinary services, improved water supply points, introduction of timely and

effective artificial insemination services to up-grade the already existing breeds,

89

launching sustainable and effective forage development program, provision of

training for the livestock holders on how to improve their production and

productivity, improving the marketing conditions, etc

5. The small size of holdings coupled with poor quality of soil and recurrent droughts do

not permit the farmers in Kamba to produce enough for the households’ without an

alternative income source. Rural households’ in the study area have very limited

room for generation of income. Hence, for these households’ to enhance their welfare

in general and food security in particular, they must have diversified access to income

alternatives to increase their purchasing power. In the face of this, provision of credit

must be taken as a measure, though not the only one, to build the capacity of farmers

to invest in the agricultural sector, such as purchase of fertilizer, pesticides, improved

seed, live and productive animals. Moreover, development strategies should be able

to identify income alternatives other than agriculture. In light of this, non-

governmental organizations that are focusing only on agriculture should also channel

their scarce resources to creation of income generating activities, trading, crafting,

etc. which would greatly help in strengthening off-farm activities which would enable

the households’ to secure their food through purchase.

6. An increase in per capita aggregate production means that the probabilities of

households’ being food secure increases. Even if farmers experience and interest to

use chemical fertilizers and improved seeds need effective awareness creation, yield

improvements were feasible through the increased use of chemical fertilizers.

Therefore, chemical fertilizers supply, price and application of them have to be

adapted to support this possibility. Government, farmer groups or organizations and

input suppliers are therefore called to provide agricultural inputs to farming

households’ in communal areas at affordable prices to enable them to increase

production and application.

90

7. One area of intervention hypothesized to improve the state of food security at

households’ level is promoting the production of cash crops (coffee and fruits). This

implies that efforts has to be made to improve income from cash crops production to

ensure food security through promoting and developing small scale and traditional

irrigation programs which intern reduce rainfall dependability and enhance the level

of households’ food security.

8. The fact that the climate of the district is dominantly semi-arid and the existence of a

serious problem of frequent crop failure caused by drought and erratic rains clearly

suggest that one of the intervention options is promoting and increasing crop

diversification to reduce crop failure that was happen due to rainfall shortage. Hence,

seeds of different variety resistance to moisture stress, pests and adaptability that can

increase productivity and yield of crops should be introduced.

9. Food aid is an assistance that comes from outside the system to support and address

the immediate food crisis. This is necessary from the viewpoint of saving lives.

However, it is not designed to give a lasting solution. Rather it destroys traditional

coping mechanisms of the society and puts it in a perpetual position to expect aid

whenever there is food shortage. This prompts the society to perpetually depend on

donors but, the link with the employment generating system would help both in

reducing dependency syndrome and contributing to local development.

10. The study suggested also that absence of market and marketing infrastructure

facilities are one of the problems of food security. Farmers close to major roads and

market centers are better encouraged to intensify production for their own

consumption as well as to produce high value crops for sale. Therefore, in order to

solve the problem of farmers in remote areas, attention should be given to the impact

of factors like poor marketing infrastructure and transport facilities. In addition,

government can improve rural infrastructure to boost households’ income through the

provision of households’ water, electricity and telecommunications. This could

increase the possibility for farmers to get right price.

91

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96

Appendices

Appendix 1:- Conversion Factors to Estimate Tropical Livestock Unit equivalents Livestock type TLU (Tropical livestock unit)

1-Calf 0.20

2-Heifer 0.75

3-Cows/Oxen 1.00

4-Horse/Mule 1.10

5-Donkey 0.70

6-Donkey (young) 0.35

7-Sheep/Goat 0.13

8-Sheep/Goat (young) 0.06

9-Chicken 0.013

Source: Storck, et at. (1991)

Appendix 2:- Conversion Factors Used to Compute Adult-Equivalent (AE) Age Category (Year) Male Female

0---1 0.33 0.33

1.1—2 0.46 0.46

2.1—3 0.54 0.54

3.1—5 0.62 0.62

5.1—7 0.74 0.70

7.1—10 0.84 0.72

10.1—12 0.88 0.78

12.1—14 0.96 0.84

14.1—16 1.06 0.86

16.1—18 1.14 0.86

18.1—30 1.04 0.80

30.1—60 1.00 0.82

> 60 0.84 0.74

Source- Source: Storck, et at. (1991)

97

Appendix 3:- Calorie value of food items consumed by sample households’ Food item Unit Kcal Food item Unit Kcal

Boqqollo Duket Kg 3782 Baqqella kolo Kg 2759

Boqqollo nifro Kg 1701 Baqqella nifro Kg 1495

Boqqollo Kolo Kg 3872 Tiqill Gommen Kg 237

Sindye Duket Kg 3623 Abesha Gommen Kg 401

Sindye kolo Kg 3916 Qeyy Shinkurt Kg 3761

Nifro ye Sindye Kg 2113 Nech Shinkurt Kg 1383

Gebs Beso Kg 3680 Orange Kg 339

Gebs Kolo Kg 3558 Papaya Kg 349

Teff Duket Kg 3589 Muze Kg 878

Mashila Duket Kg 3774 Mango Kg 438

Enset Kg 1960 Yebere siga Kg 1774

Kocho Kg 2111 Yefiyel siga Kg 2000

Bula Kg 1805 Yebeg Siga Kg 1529

Irish potato Kg 897 Milk Lt 737

Cassava Kg 1240 Coffee+milk Lt 180

Yam Kg 850 Egg No 1529

Taro Kg 1083 Sugar Kg 3850

Sweet Potato Kg 1342 Shenqura Ageda Kg 953

Adengwarrye Kg 1703 Qibye Kg 7604

Ater suro Kg 3522 Zeyt Lt 8964

Source-EHNRI Part III (1968-1997)-Food consumption table for use in Ethiopia

98

Appendix4. Summary of the Survey Questionnaire

General Information

Date of Interview, Name of the enumerator, Name of Keble, Signature, Start and end time

PART I. Households’ roster

Name, sex, age, educational level of the households’ members, marital status, main current activity of the

households’ members, religion

SECTION 2: households’ food consumption

What type and quantity of foods were prepared for consumption in this households’ in the last seven

days?

We would like to ask you some questions about food consumption in this households’ in the last seven days. These questions concern to the quantity of foods prepared for consumption

Food type Local Unit

Local unit estimated to kg

Conversion into kilos

Adjustment for processing

Number of calories available for consumption

Beqqollo Duket

Listing all foods commonly eaten in the area

Section 3- Food consumption habit

How many meals did the adults in your HH ate yesterday? (Adult, above 15 years)?

How many meals did the children in your HH ate yesterday (children, under 15 years)

What has been the trend of food availability for your households’ (family) during the last 5 years?

Food item Did your house hold consume this food item in the past 7 days

Yes---1

No-----0

Number of days the food item was eaten in the last 7 days

How much in total did your HHconsume (in kg) or local nit)

How much came

from purchase

How much came

from own production

How much came

from gift

Wheat

Maize

Irish potato

Sweet potato

99

Barely

Section 4- Land use information Does the households’ own agricultural land? ------------If Yes----1, if No-------0 What is the total area of the agricultural land? ------------Hectare----------- Timade----------Other Do you think that your piece of land is enough to support your family? ------ Yes----1, no-----0 What is the quality of your Soil relative to other farmers? ------------If Good-----1 if Poor------0 Section 5- Crop production trend What major crops are produced using your land? (Order by priority and large area allocation) Rank of crops Name of the crop Area allocated in timade

1st

2nd

Section 6-Irregation application

Do you have irrigation land? ................if Yes---1, if No-----0

If yes how much is it? ------------Hectare or--------------Timade-------------Others (specify).

What crops are produced using irrigation?

Section 7-Crop production

Is your own production enough for your households’? -----------If Yes------1, if No--------0

If yes, for how many months do you consume your own production during normal production?

For how long can you feed your family financially after now in the future?

If you can’t produce enough food for your family what are the problems you encountered?

Problems encountered Very serious Serious Less serious Not a problem

Small land holding

In adequate rainfall

Do you produce both in belg and meher seasons? ----------ifYes------------1,if No-------------0 Which season production gives you the highest product? -------- Belg--------1,Meher------- 0 If yes, what are your major crops you cultivate? Type of annual major crop

Area allocated in timade

In Belg season In meher season

If the answer for question is No, what are possible reasons? Possible reasons Rank the reasons

No enough rainfall

100

We fear crop failure

A crop does not give enough output

Did you plant in your farmland drought resistant crops? ------- If Yes--------1, if No---------0 If yes what are these and their area allocated? Type of drought resistant crop Yes No Area allocated in timade

Inset

Cassava

Sorghum

Sweet potato

Averagely how many times do you cultivate (weed) your seasonal crops after sawing? Type of annual major crops Number of weeding until harvest

Maize

Wheat

Section 8-Forestry soil and water conservation

Is your farm prone (lying face down) to erosion? -----------If Yes-----1, if No-----0

What portion of your farmland is affected by erosion?

Portion affected by erosion Yes No

none

All

half

More than half

Has erosion affected your farm severely before? -----------If Yes----1 if No------0 How do you see the level of erosion on your farming plots since you started farming? Level of erosion Yes No

Very sever

Severe

Mino

No problem

How serious is the decline in soil fertility, on your main plot, since you started farming?

101

decline in soil fertility Yes No

Very severe

Severe

Minor

No problem

Do you think that soil erosion will affect your farm in the future if situations remain Unchanged? Is there any soil and water conservation structure done on your farm land? --- if Yes---1,if No--- If yes, is that done by your own or other body?

Who done the structure Yes NO

By you

By Government body

By NGO’S

Section 9- Use of modern agricultural inputs

Do you use improved seed and chemical fertilizer for your agriculture?- --- If Yes---1, if No—0

If yes please tell me the amount?

no Type of crop Area cultivated in timade

Amount of chemical fertilizer used

Improved seed used in kg

Local fertilizer(compost)used in Kg

DAP UREA

1 Maize

2 wheat

If you can’t apply improved seed what is your main reasons? Reasons Rank

Price is high for it

don’t have enough money to purchase it

If you can’t apply chemical fertilizer what is your main reasons? Reasons Rank

Price is high for them

I don’t have enough money to buy it

Section 10-Agricultural extension services

102

Has your households’ received extension service from any government? --- if Yes ---1. If No-----0 Are there agricultural development agents (DA) in your Peasant Association? - if Yes --1. if No-Has the development agent visited your farm during the year 2002/2003 E.C--if Yes --1. If No--0 Do you use oxen for your farm operation? --------If Yes-----1, if No-----0 If yes, how many oxen’s do you have in number that helps to plow? ----------------------- If yes, to above question how many times? Number of visit Yes No

One time

Two times

What was the purpose of the visit? purpose of the visit Yes No

To give advice on crop production

To give advice on animal production

Section11-Access to various services Type of service Unit of measurement Total service unit

How far is the market that you can buy and sell food from your home

km minute

What other means do you use to fulfill the food requirements of your family Other than production? Means used to fulfill the food gap yes NO Food purchase Food aid Section 12-Marketing and credit Did your family buy any food from the market this year? ---------- -if Yes----------1ifNo---------0 If yes in which months do you buy more usually, please tell me the months? If you are buying food items from markets, is the price increasing or decreasing? _________ Approximately how much did you spent to buy food items last six months? ------------birr

Which food item do you purchase mostly from the market? Type of crop bought yes No

Cereals(maize, wheat, barley, sorghum, teff)

Root and tubers (cassava, yam, taro, enset)

What is your means for transporting goods? Means of transportation Yes No

pack animals

human

Is there any credit facility /institute in this area /woreda?------------if Yes-----1, ifNo-----0

103

This years, have you taken out a loan?-----------if Yes ----1;if No ---- 0 Are you ready to borrow money from credit institutes?----------if Yes----1, if No------0 If no what are the possible answers? Possible reasons Yes No

I don’t have plane what to do

I fear any government intervened credits

Do you have saving habit? ----- If Yes----1, ifNo---0 if yes amount saved last year ___ birr.

Is your family participating in safety net programme? ---------If Yes-----1, if No------0

Is your family included in any food security programme? -------if Yes---1, if No---0

If yes, in which programme? ----------------------------------------- How do you like to sustain your family in the future?

Means to sustain yes NO

Cultivation

Livestock production

Engage in other off- farm activities

Are you happy living in this agro-ecology? -------------If Yes---1, if No----0

If not what are the main reason that makes you not happy?

reasons rank

Having small land holding

decreased soil fertility and low production

existence of disease

Do you participate always in all public meetings? ---------If yes-----1 if No-----0 Does your family practice in family planning? ----------If Yes------1, if No------0 If yes which family planning methods do you use? Type of family planning Yes No

Pills

Injection

Condom

104

If you do not use family planning, reasons are Main reasons Yes No

Causes health problem

Section13- Livestock production and management

Does your family have livestock’s? ---------If yes-----1, if No-------0. If yes please give the list.

Type of livestock

Number currently owned

Current market estimate

Number not owned but cared for(adera yetkemet)

Number owned but away ithothers(adera yetesete)

Total owned

Total market estimate

Bulls/oxen

Young bulls

What is area of land allocated for animal feed in Timade? -----------------

Which animal disease repeatedly occurs in your area?

Rank Name of animal disease Time of occurrence in months

1st

2nd

Did you spend for veterinary services during the last 12 months? -----If Yes----1, if No-----0

If yes how much was the total cost for veterinary services? -------------------------------birr

Is there any animal death in last 6 months from your home? ---------If Yes----1, if No-----0

If yes how many and estimated price in market? Number of animal’s dead---------Estimated market price in birr------

What is the main mode of feeding for your livestock?

Mode of feeding yes No

Open grazing

Intensive lot feeding

What is the main source of feed for your live stokes?

Main source of feed yes No

Open communal range land

Private Grazing land

Did you purchase feed for your livestock during the last 12 months? ----if Yes---1,if No---0

Section14 – households’ income

Source of income Unit quantity Unit price Total sale in birr

crop sale

105

crop sale

Animal sale

Section 15-Off- farm income

Has anyone from your households’ migrated in the past year? -------if Yes...... 1, if No.........0 if yes where did they go? Place of migration yes No

Within woreda

Outside woreda.

In which season did they go mostly?

Time of migration yes No

Kola harvest season

Does your family have any job other than agriculture that increase households’ income? If yes what are they?

Type of activity Yes No

Hand craft (pottery, Blacksmith ,fencing)

Trade in livestock or livestock products

Trade in grain and others

Selling beverage

Wage work

Would you please tell total family off-farm income? ---------------birr

Section 16 -Copping mechanisms

How do your households’ used to cope during crop failures?

Type of cooping Yes No Rank

Sale of livestock

Reduce the number of meals

Wage employment

Eating wild food

106

STATA-10 OUTPUTS

Note: 61 failures and 36 successes completely determined. _cons ----11111111....55550000333388887777 4444....555588880000111177777777 ----2222....55551111 0000....000011112222 ----22220000....44448888000088886666 ----2222....555522226666888899992222 MONTH ....8888111166668888555522222222 ....3333777799990000555599991111 2222....11115555 0000....000033331111 ....0000777733339999000099999999 1111....555555559999777799994444 landqulity 8888....333322221111222277772222 2222....222288880000888811112222 3333....66665555 0000....000000000000 3333....888855550000999966662222 11112222....77779999111155558888 saving ....0000000011110000111177774444 ....0000000000006666333300002222 1111....66661111 0000....111100006666 ----....0000000000002222111177777777 ....0000000022222222555522225555extensions~t 5555....222266666666666644446666 2222....000055554444111166663333 2222....55556666 0000....000011110000 1111....222244440000555566661111 9999....222299992222777733331111participa~1n 7777....111188883333111144442222 1111....888888884444000022222222 3333....88881111 0000....000000000000 3333....444499990000555522228888 11110000....88887777555577776666accesstoro~m ----....000077775555222288886666 ....0000444433339999222233336666 ----1111....77771111 0000....000088887777 ----....1111666611113333777744446666 ....0000111100008888000022227777technologi~d 6666....444477775555777722226666 1111....777766660000000055557777 3333....66668888 0000....000000000000 3333....000022226666000077777777 9999....999922225555333377774444amountoffo~d ....000000008888000011113333 ....0000111188880000555588883333 0000....44444444 0000....666655557777 ----....0000222277773333888800006666 ....0000444433334444000066665555educationo~d ....5555111111118888666666666666 ....2222666600002222666688881111 1111....99997777 0000....000044449999 ....0000000011117777555500005555 1111....000022221111999988883333totalofffa~e ....0000000022224444777799991111 ....000000000000777788882222 3333....11117777 0000....000000002222 ....0000000000009999444466664444 ....0000000044440000111111118888livestocko~u 1111....666622225555777766663333 ....3333777722228888777799992222 4444....33336666 0000....000000000000 ....8888999944449999333333332222 2222....333355556666555599993333 farmsize 9999....999911112222222299994444 2222....777700005555333333332222 3333....66666666 0000....000000000000 4444....666600009999999944441111 11115555....22221111444466665555 familysize ----5555....444422222222777711119999 1111....000066660000999933332222 ----5555....11111111 0000....000000000000 ----7777....555500002222111100007777 ----3333....33334444333333333333 foodsecuri~c Coef. Std. Err. z P>|z| [95% Conf. Interval] Robust

Log pseudolikelihood = ----8888....8888111155556666222233335555 Pseudo R2 = 0000....9999333344443333 Prob > chi2 = 0000....0000000000000000 Wald chi2(11113333) = 55553333....33333333Logistic regression Number of obs = 222200000000

VIF test output

Mean VIF 1111....33338888 amountoffo~d 1111....11110000 0000....999900009999111199994444extensions~t 1111....11116666 0000....888866661111222211115555educationo~d 1111....11117777 0000....888855555555888811115555technologi~d 1111....22220000 0000....888833336666777755556666totalofffa~e 1111....22226666 0000....777799990000555522227777 saving 1111....22227777 0000....777788886666777700003333 landqulity 1111....22228888 0000....777788884444111177776666numberofmo~h 1111....22229999 0000....777777778888111155559999accesstoro~m 1111....44442222 0000....777700004444888833336666 familysize 1111....44442222 0000....777700002222444488881111participa~1n 1111....55556666 0000....666644441111888844443333 farmsize 1111....88887777 0000....555533335555999955551111livestocko~u 2222....00001111 0000....444499996666666688886666 Variable VIF 1/VIF

. vif

107

Contingency coefficient

foodsecuri~c ----0000....0000000055559999 ----0000....0000222299993333 0000....5555888833333333 0000....3333888866660000 1111....0000000000000000 technologi~d 0000....0000777755550000 0000....1111555511114444 0000....2222333322221111 1111....0000000000000000 participa~1n ----0000....1111444433337777 0000....0000888855557777 1111....0000000000000000 extensions~t ----0000....0000777755559999 1111....0000000000000000 landqulity 1111....0000000000000000 landqu~y extens~t parti~1n techno~d foodse~c

Odds Ratio

Note: 61 failures and 36 successes completely determined. MONTH 2222....222266663333333366664444 ....8888555577779999444488888888 2222....11115555 0000....000033331111 1111....00007777666677771111 4444....777755557777888844443333 landqulity 4444111111110000....333388885555 9999333377775555....000011114444 3333....66665555 0000....000000000000 44447777....00003333888833332222 333355559999111188880000....8888 saving 1111....000000001111000011118888 ....0000000000006666333300008888 1111....66661111 0000....111100006666 ....9999999999997777888822223333 1111....000000002222222255555555extensions~t 111199993333....777766665555 333399998888....0000222244448888 2222....55556666 0000....000011110000 3333....444455557777555555551111 11110000888855558888....8888participa~1n 1111333311117777....00004444 2222444488881111....333333332222 3333....88881111 0000....000000000000 33332222....88880000333322226666 55552222888877778888....77775555accesstoro~m ....9999222277774444777788882222 ....0000444400007777333388882222 ----1111....77771111 0000....000088887777 ....8888555500009999777733332222 1111....000011110000888866661111technologi~d 666644449999....1111999900001111 1111111144442222....666611112222 3333....66668888 0000....000000000000 22220000....6666111166662222 22220000444444442222....55556666amountoffo~d 1111....000000008888000044445555 ....0000111188882222000033335555 0000....44444444 0000....666655557777 ....9999777722229999999900009999 1111....000044444444333366662222educationo~d 1111....666666668888444400003333 ....444433334444222233332222 1111....99997777 0000....000044449999 1111....000000001111777755552222 2222....777777778888666699999999totalofffa~e 1111....000000002222444488882222 ....000000000000777788884444 3333....11117777 0000....000000002222 1111....000000000000999944447777 1111....00000000444400002222livestocko~u 5555....000088882222222299995555 1111....888899995555000088882222 4444....33336666 0000....000000000000 2222....444444447777111177772222 11110000....55555555444499993333 farmsize 22220000111177776666....99991111 55554444555588885555....22225555 3333....66666666 0000....000000000000 111100000000....4444777788883333 4444000055551111777700001111 familysize ....0000000044444444111155551111 ....0000000044446666888844442222 ----5555....11111111 0000....000000000000 ....0000000000005555555511119999 ....0000333355553333111199992222 foodsecuri~c Odds Ratio Std. Err. z P>|z| [95% Conf. Interval] Robust

Log pseudolikelihood = ----8888....8888111155556666222233335555 Pseudo R2 = 0000....9999333344443333 Prob > chi2 = 0000....0000000000000000 Wald chi2(11113333) = 55553333....33333333Logistic regression Number of obs = 222200000000

108

Marginal effect table

(*) dy/dx is for discrete change of dummy variable from 0 to 1 MONTH ....0000000044449999111177773333 2222....77772222 landqulity* ....8888444477771111444400005555 ....11118888 saving 6666....11112222eeee----00006666 555577773333....888877775555extensionservicegotservice1donot* ....000011110000999988885555 ....888888885555participatininpublicmeetingyes1n* ....1111000000004444444422228888 ....555599995555 accesstoroadeinkm ----....0000000000004444555533332222 11118888....9999888822225555technologicaladoptionusedfertand* ....0000444477775555333322227777 ....666677775555 amountoffoodaidrecived ....0000000000000000444488882222 44443333....4444 educationofhhhead ....0000000033330000888811113333 2222....33334444 totalofffarmincome ....0000000000000000111144449999 666611117777....3333 livestockownedbytlu ....0000000099997777888866668888 4444....77774444444444443333 farmsize ....0000555599996666777700002222 1111....11119999111111118888 familysize ----....0000333322226666444433338888 5555....99997777 variable dy/dx X = ....0000000066660000555566665555 y = Pr(foodsecuritystatusesecured1insec) (predict)Marginal effects after logistic