Food Security Status and Its Determinants Among Rural Households in Oda

FOOD SECURITY STATUS AND ITS DETERMINANTS AMONG

RURAL HOUSEHOLDS IN ODA BULTUM DISTRICT, WEST

HARARGHE ZONE, OROMIA NATIONAL REGIONAL STATE,

ETHIOPIA

MSc THESIS

AHMED MOHAMMED

JUNE 2021

HARAMAYA UNIVERSITY, HARAMAYA

Food Security Status and Its Determinants among Rural Households in Oda

Bultum District, West Hararghe Zone, Oromia National Regional State,

Ethiopia

A Thesis Submitted to the School of Agricultural Economics and

Agribusiness

Postgraduate Program Directorate

HARAMAYA UNIVERSITY

In Partial Fulfillment of the Requirements for the Degree of MASTER OF

SCIENCE IN AGRICULTURAL ECONOMICS

Ahmed Mohammed

June 2021

Haramaya University, Haramaya

HARAMAYA UNIVERSITY

POSTGRADUATE PROGRAM DIRECTORATE

I hereby certify that I have read and evaluated this Thesis entitled “Food Security Status and Its Determinants among Rural Households in Oda Bultum District, West Hararghe Zone, Oromia National Regional State, Ethiopia” prepared under my guidance by Ahmed Mohammed

Abdurehim. I recommend that it be submitted as fulfilling the thesis requirement. Ketema Bekele (PhD) ______Major -Advisor Signature Date Mohammed Aman (Assist. Prof) ______Co-Advisor Signature Date

As member of the board of examiners of the MSc thesis open defense examination, I certify that I have read and evaluated the thesis prepared by Ahmed Mohammed and examined the candidate. I recommend that the thesis be accepted as fulfilling the thesis requirements of degree of masters in Agricultural Economics.

Million Sileshi (PhD) ______Chairperson Signature Date Kedir Jemal (PhD) ______Internal Examiner Signature Date Abebaw Shimeles (PhD) ______External Examiner Signature Date

Final approval and acceptance of the thesis is contingent upon the submission of its final copy to the council of postgraduate program directorate (CPPD) through the candidates department or postgraduate program committee (CD or PPC).

DEDICATION

I dedicate this thesis manuscript to my mother Hindi Usman and father Mohammed Abdurehim, for nursing me with love and for their sacrifice in the success of my life.

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STATEMENT OF THE AUTHOR

By signature below, I declare and affirm that this thesis is my original work. I have followed all ethical and technical principles of scholarship in the preparation, data collection, data analysis and compilation of this thesis. Any scholarly matter that is included in the thesis has been given recognition through citation.

This thesis is submitted in partial fulfillment of the requirements for a master degree at the Haramaya University. The thesis is deposited in the Haramaya University Library and is made available to borrowers under the rules of the library. I solemnly declare that this thesis has not been submitted to any other institution anywhere for the award of any academic degree, diploma or certificate.

Brief quotations from this thesis may be made without special permission provided that accurate and complete acknowledgement of the source is made. Requests for permission for extend quotations from or reproduction of this thesis in whole or in part may be granted by the head of the school or department when in his or her judgment the proposed use of the material is in the interest of scholarship. In all other instances, however, permission must be obtained from the author of the thesis.

Name: Ahmed Mohammed Signature: ______Date: ______School: Agricultural Economics and Agribusiness

LIST OF ABBREVIATIONS AND ACRONYMS

ADB Africa Development Bank AE Adult Equivalent CSA Central Statistics Agency CSI Coping Strategy Index DF The Development Fund DFID Department for International Development EC European Commission ETB Ethiopian Birr EU European Union FAO Food and Agriculture Organization of the United Nation FCS Food Consumption Score FDRE Federal Democratic Republic of Ethiopia FGD Focus Group Discussion FGT Foster Greer Thorbeke FNS Food and Nutrition Security FSS Food Security Strategy IFAD International Fund for Agricultural Development Kcal Kilo calorie NEPAD New Partnership for Africa‟s Development OBDAO Oda Bultum District Administrative Office OLS Ordinary Least Square TLU Tropical Livestock Unit UNDP United Nations Development Program USAID United States Agency for International Development WFS World Food Submit

BIOGRAPHICAL SKETCH

The author was born in January 1993 in Miesso district of west hararghe zone, oromia national regional state, Ethiopia. He attended his elementary education at Miesso elementary school at Miesso district and his high school at Miesso high school and his preparatory education at Chercher secondary and preparatory school in Chiro district. After successfully passing the Ethiopian university entrance exam; he joined Addis Ababa University in October 2013 and graduated with B.Sc. Degree in Agricultural Economics in July 2015. Soon after his graduation; he was employed at Oda Bultum district as expert of Agriculture and Natural Resource Office. After serving for three years as expert, he joined Haramaya University in 2018 to pursue his M.Sc. study in Agricultural Economics.

ACKNOWLEDGEMENTS

This thesis is the result of the encouragement and support of many individuals and organizations. First of all, I express my deepest grateful thanks to my advisors Ketema Bekele (PhD) and Mohammed Aman (Assist. Prof) for their professional suggestions, invaluable and constructive comments, and intellectual encouragement they gave me from the early design of the research proposal to the final work of this thesis.

My best appreciation goes to Oda Bultum District for granting me the sponsorship and the opportunity to join Haramaya University for my study. I extend my special appreciation for all Haramaya University Agricultural Economics staff members for sharing their knowledge during my stay.

I never forget to give best regard to enumerators who made differential attitude and technicality during the data gathering. Many thanks also go to sampled households and the district Agricultural Office staff members for their provision of valuable information requested.

Finally, I express my special thanks to my beloved family and friends for their moral supports that help me successfully finalize my thesis work.

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TABLE OF CONTENTS

DEDICATION III

STATEMENT OF THE AUTHOR IV

LIST OF ABBREVIATIONS AND ACRONYMS V

BIOGRAPHICAL SKETCH VI

ACKNOWLEDGEMENTS VII

LIST OF TABLES XI

LIST OF FIGURES XII

LIST OF TABLES IN THE APPENDICES XIII

ABSTRACT XIV

1. INTRODUCTION 1

1.1. Background of the Study 1

1.2. Statement of the Problem 2

1.3. Research Questions 4

1.4. Objectives of the Study 4

1.5. Significance of the Study 5

1.6. Scope and Limitation of the Study 5

1.7. Organization of the Thesis 6

2. LITERATURE REVIEW 7

2.1. Basic Concepts and Definitions 7

2.2. Dimensions of Food Security 8

2.2.1. Food availability 8 2.2.2. Food accessibility 9

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2.2.3. Food utilization 9 2.2.4. Stability 10

2. 3. Food Security Indicators and Measurements 11

2.4. Empirical Evidences 15

2.5. Conceptual Framework 17

3. RESEARCH METHODOLOGY 20

3.1. Description of the Study Area 20

3.1.1. Location 20 3.1.2. Population 20 3.1.3. Climate, land use and production activities 21

3.2. Data Type, Sources and Methods of Data Collection 22

3.2.1. Data type and sources 22 3.2.2. Methods of data collection 23

3.3. Sampling Techniques and Sample Size Determination 23

3.4. Methods of Data Analysis 24

3.4.1. Descriptive analysis 24 3.4.2. Econometric model 26

3.5. Definition of Variables and Working Hypotheses 29

3.5.1. Dependent variable 29 3.5.2. Independent variables 29

4. RESULTS AND DISCUSSIONS 36

4.1. Household Food Security Status 36

4.2. Incidence, Gap and Severity of Food Insecurity 37

4.3. Descriptive Statistics 39

4.3.1. Descriptive statistics of continuous variables 39

4.3.2. Descriptive statistics of categorical variables 42

4.4. Econometric Model Results and Discussions 44

4.4.1. Regression diagnostics 44 4.4.2. Determinants of household food security status 45

5. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS 50

5.1. Summary 50

5.2. Conclusions and Recommendations 51

6. REFERENCES 54

7. APPENDICES 64

LIST OF TABLES

Table Page 1. Total number of sample household heads 24 2. Summary of definition of variables and hypothesis 34 3. Mean differences test of daily calorie intake by food security status 36 4. Incidence, gap and severity of food insecurity 38 5. Descriptive statistics of continuous variable 41 6. Descriptive statistics of categorical variable 44 7. Determinants of food security status 48

LIST OF FIGURES

Figure Page 1. Conceptual framework of the study 19 2. Geographic map of Oda Bultum district 21 3. Food security status 37

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LIST OF TABLES IN THE APPENDICES

Appendix Table Page

1: Conversion factors used to compute AE 64 2: Conversion factors used to compute TLU 64 3: Conversion factors used to estimate Kcal of food items 64 4: Multicollinearity test 65 5: Link test of model specification 66 6: Hosmer-Lemeshow test 66

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ABSTRACT

Food security is one of the critical concerns and top priority of policy agenda for developing countries. Having clear picture on food security status and its determinants helps policy makers to devise appropriate policies that enhance food security. Hence, this study aims to determine the food security status of the households, status, gap and severity of food insecurity among rural households and its determinants in Oda Bultum district of West Hararghe zone, Oromia National Regional State. The data for this study were collected from primary and secondary sources. Primary data were collected from randomly selected 365 sample households by using multistage sampling procedure and secondary data were obtained from various sources. The data were analyzed using descriptive statistics, Foster-Greer-Thorbecke (FGT) and probit model. The survey results indicated that 38.9% sampled households were food secured whilst 61.1% were food insecure. Further analysis of Probit regression revealed that; sex of household head, educational level, household size, donkey ownership, cash crop production, off/non-farm income, income, access to irrigation and frequency of extension contact significantly increased probability of being food secure. This study recommends that rural households should be encouraged to increase off/non-farm income, work on household size by creating awareness, increasing frequency of extension contact, increasing cash crop productivity, increasing access to irrigation, increasing income, donkey possession and improvement of the educational level for the household heads in order to enhance households’ food security status in the study area.

Key words: Food security, Agro-pastoralist, Sedentary faming, Probit, Oda Bultum.

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1. INTRODUCTION

1.1. Background of the Study

These days, food insecurity is a global problem. Acknowledging that, the world is struggling to address since decades back. However, it is still far away from a decisive victory. In this regard, FAO (2016) indicated that despite undeniable progress in reducing rates of undernourishment and improving levels of nutrition and health, about 800 million people are chronically hungry. Among 800 million globally under chronically hunger people, 239 million are from Sub-Saharan Africa (SSA) and nearly two billion people are affected by hidden hunger (WHO, 2016). Further, FAO (2016) predicts that the world will host about 653 million undernourished people even in 2030 if no additional efforts are made to promote pro-poor development.

More than one in four Africans are undernourished. An environmental change brought about by altered weather patterns has the potential to seriously further adversely impact on food security. In Africa‟s most vulnerable regions, SSA makes up the bulk (FAO, 2015). As 90% of food in SSA grown under rain-fed agriculture, food production in the region has become vulnerable to changes in weather conditions.

Researches evidenced that Ethiopia is among the countries in SSA countries which has been repeatedly mentioned in connection with food security problem. For instance, MoFED (2013) reported that among the varieties of shocks Ethiopian households face food insecurity and food prices shocks are the most common ones. UNDP (2018) also pinpointed that Ethiopia is among the poorest and most food insecure countries of the world where 23% of the population live below the poverty line.

Nearly 27 million Ethiopians become food insecure as a result of 2015 El Niño drought and 18.1 million dependents on relief food assistance in 2016 (Abduselam, 2017). Temesgen et al. (2016) also estimated that an average of 4.5 million Ethiopians were left to emergency food handout from 2011 through 2015 due to climate related calamites. Due to the continued El Nino from 2015 onwards, Ethiopia is facing one of the worst crises with an estimated 10.2 million

people dipping in need of food aid (FAO, 2016).

On top of environmental changes, rapid population growth and backward smallholder farming system challenged achievement of food security and poverty reduction efforts in Ethiopia. An annual increment of two million people is a great challenge to the economy‟s ability to provide proper services and the environment (FAO, 2012). Smallholder farming is the dominant livelihood activity for the majority of Ethiopians, but it is also the major source of vulnerability to poverty and food insecurity (Brown and Teshome, 2015). Even though food insecurity is an overriding problem of most developing countries, Ethiopia requires empirical evidence pertinent to food security policy formulation and implementation (Degye et al., 2013). To combat food insecurity problem, the Ethiopian government has designed food security policy and strategy which was first issued in 1996 within the framework of Ethiopia‟s Poverty Reduction Strategy (FDRE, 1996; 2004).

An empirical study conducted on household food security situation in central Oromia region of Ethiopia reported that 37.93% of the investigated households were food insecure (Degefa and Furgasa, 2016). The study found out that the major factors constraining households‟ food production are high fertilizer price, shortage of farm land, erratic rainfall pattern, water logging, crop disease and insect pests, lack of improved seed supply, and lack of improved farm machineries. Specific to West Hararghe zone, Fekeda et al. (2015) conveyed that the majority (67.1%) of households were food insecure.

1.2. Statement of the Problem

Ethiopia is one of the most food insecure and famine affected countries. A large portion of the country‟s population has been affected by food insecurity. Food insecurity situation in the country is linked to recurring of food shortage and famine, which are associated to recurrent drought (ADB, 2014). According to UNDP (2018), more than 23% of the Ethiopian population lives below the poverty line and above 20 million people are undernourished.

Food security status at national level has shown improvements over the last two and half decades. Food insecurity at national level had declined from approximately 52% in 1980s to 43% in

1995/96, but stayed almost the same at about 44% in 2003. From this status, it had declined to about 39% in 2004/05 and further to about 36% in 2005/06. Then, it came down to 33% in 2006/07, 28% in 2009/10 and 23.5% in 2018 (UNDP, 2018).

The government of Ethiopia, WFP and other development partners work together to increase families‟ long-term resilience to food shortages. In 2005, productive safety net program (PSNP) was established and aimed at enabling the rural poor facing chronic food insecurity to resist shocks, create assets and become food self sufficient. Ethiopia‟s PSNP is a development oriented social protection program aimed at solving the chronic food needs of rural households in the country. In 2005, the program commenced by covering four regions of the country (Tigray, Amhara, Oromia and SNNPR) aiming to reach more than 1.6 million households (5 million people) in 263 districts identified as chronically food insecure areas (Gilligan et al., 2009). By the end of 2010, the number of peoples whose PSNP beneficiaries had reached over 7.8 million spanning over 300 districts in eight regions across the country (Kwadwo et al., 2013).

Deferent researchers and organizations indicated that, the main causes of food insecurity are high population growth rate, high reliance on small size and rainfall agricultural land holdings, dramatic variation in rainfall and repeated environmental shocks, lack of access to input, lack of access to credit, high susceptibility to drought, limited access to basic service, lack of access to market, land degradation and decreased productivity, lack of income generation opportunity and alternatives, lack of access to technology, lack of access to information on market and agricultural technology (EU, 2012; Hana and Dereje, 2016).

However, there are significant variations among regions and among districts of a single region in the extent, cause, vulnerability and coping strategies against food insecurity (Yisihake et al., 2016). As a result, in order to combat threats of food insecurity by ensuring food security, detailed understanding of the socio-economic condition of the group affected by it, and the determinant factors and how households cope with the problem of food insecurity is critically important (NEPAD, 2013).

As already stated above, the problems of food insecurity take particular forms in its extent, causes and consequences at different level of analyses. Despite the efforts made by the government of Ethiopia, WFP and other development partners, food insecurity problem remains a challenge in Ethiopia in general and in Oda Bultum district in particular. In line with this, Oda Bultum district is one of the food insecure districts, which the government has taken as a pilot district for the implementation of PSNP starting from 2005 up to now.

However, in this district there were few empirical studies conducted on households‟ food security status, its determinants and coping mechanisms based on the agro-ecology. Hence, this study was intended at filling this research gap by considering the livelihood of the district to identify the factors contributes to household food security in Oda Bultum district, West Hararghe Zone of Oromia National Regional State, Ethiopia.

1.3. Research Questions

The study attempted to answer the following four research questions. 1. What is the current status of food security among rural households in the Oda Bultum district? 2. What are the status, gap and severity of food insecurity among rural households in the study area? 3. What are the major determinants of households‟ food security in the study district?

1.4. Objectives of the Study

The general objective of the study was to assess rural households‟ food security status in Oda Bultum district. Specifically, the study was to: 1. measure the current status of food security among rural households in Oda Bultum district;

2. estimate the status, gap and severity of household food insecurity in the study area 3. determine factors that influence household food security status in the study area.

1.5. Significance of the Study

Findings of the study were expected to give clear understanding of household food security in the study area to help policy makers and planners in the formulation of appropriate policies that were dedicated in alleviating food insecurity. Moreover, this study provides necessary information for government officials, extension personnel, and development planning program agencies in designing, targeting, and implementing of programs for these people by providing possible policy options that could improve the food security needs in the study area.

Local and international NGOs interested in promoting agro-pastoral and sedentary farming development in the study area will be benefited from the findings of the study and it will also serve as a bench mark for researchers and others interested in the topic to undertake further study. Last but not least, little work has been done about household food security in the study areas. Thus, it will narrow the knowledge gap about food security and to add something to the existing literature.

1.6. Scope and Limitation of the Study

This study was focused on food security status of households, status, gap and severity of food insecurity among rural households and its determinants in the rural parts of Oda Bultum district in West Hararghe Zone Oromia National Regional State. This study was focused on the four Gandas (Kebeles) of the district. Household caloric acquisition was used as food security measurement for this study.

According to the traditions of the area, counting assets and household members is someway intolerable. However, this study attempted to minimize the unwillingness of the respondents in issues like assets holding and household size through using local enumerators who had familiarity of the cultural setting of the social system.

1.7. Organization of the Thesis

This thesis has five chapters. Chapter one deals with the background information, statement of the problem, objectives, significance and scope and limitations of the study. In chapter two, review of literature that focused on the basic concepts and definitions, dimension of food security, food security indicators and measurements, empirical studies on determinants of food security and conceptual framework of the study were presented. In chapter three, description of the study area, data type, source and methods of data collection, sampling technique and sample size, method of data analysis and definition of variables and hypotheses are presented. In chapter four, results and discussions of the research outcomes are presented and finally chapter five presents summary, conclusions and recommendations of the study.

2. LITERATURE REVIEW

In this chapter, relevant literatures on the subject of the study are reviewed. The basic concepts and definitions of food security, agro pastoral and sedentary farming livelihoods in relation to food security and factors that could influence food security are discussed in detail. Moreover, different views on food security are discussed briefly and problems faced by communities in developing countries are highlighted. Finally, a discussion on the concept of coping strategies and empirical reviews on determinants of food security are provided.

2.1. Basic Concepts and Definitions

Food security- has been defined differently by different authors and organizations. The concept and definition of food security has been changed since its introduction in the early 1940s (CFS, 2012). The most careful redefinition of food security was negotiated through an international consultation in preparation for the World Food Summit in November 1996. Accordingly, 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. Moreover, in 1996 the World Food Summit gave three dimensions of food security include food availability, accessibility and utilization (FAO, 1996). Latterly it has included stability of supply as a fourth food security dimension (FAO, 2008). Therefore, in this study food security was defined as sufficient food consumed by the household or sufficient amount of calorie available at household level.

Food insecurity- is a concept originated in the mid-1970s, in the discussions of international food problems at a time of global food crisis. At that time, food insecurity was mostly concerned with national and global food supplies (Frankenberger, 1992). With regard to its (food insecurity) cause, the food crisis in Africa in the early 1970's stimulated a major concern on the part of the international donor community regarding supply shortfalls created by production failures due to drought and desert encroachment as the major cause. Food supplies shortfall as the major cause of food insecurity was given weight at the 1974 World Food Conference. This understanding of the concept of food insecurity was manifested by the

definition that was given in the World Food conference of 1974. According to the World Food Conference of 1974 food insecurity was defined as: „Unavailability at all times of adequate world food supplies of basic foodstuffs to sustain a steady expansion of food consumption and to offset fluctuations in production and prices‟ (Clay, 2002).

According to FAO (2000), food insecurity is a situation that exists when people lack secure access to sufficient amounts of safe and nutritious food required for normal growth and development and an active and healthy life. It may be caused by the unavailability of food, insufficient purchasing power, inappropriate distribution, or inadequate use of food at the household level. Food insecurity, poor conditions of health and sanitation and inappropriate care and feeding practices are the major causes of poor nutritional status.

Agro-pastoralist- is the households which obtain more than 25 percent but less than 50 percent of their gross incomes from livestock on communal grazing land and more than 50 percent from cropping activities are defined as agro-pastoral (Swift, 1988). One where crop production is combined with the rearing of the livestock also called agro-pastoralist. Sedentary farming is a method of agriculture in which the same land is farmed every year.

2.2. Dimensions of Food Security

To examine food security whether a change from one status to others, it is crucial to see from the view point of food security dimensions. Cognizant of the FAO (2000) definition, literature such as Gross et al. (2000), LIFT and USAID (2011), Upton et al. (2015), and Tawodzera (2010) identified four dimensions or components of food security: availability, access, utilization and stability.

2.2.1. Food availability

According to FAO (2013), food availability is a dimension of food security that plays a prominent role. Enough supply (availability) of food to a population is a necessary but not sufficient condition for food access. This is really the case when the national food supply or availability could not guarantees the individual household to access that supply unless and

otherwise that specific household has the means, the resources and the purchasing power to access that supply. Thus this rests on the statement that a household access to resources leads to that specific household food availability or supply by enabling that household to be able to produce his own food or to buy and use his food requirement.

Food availability which means food must be available in sufficient quantities and on a consistent basis. It addresses the supply side of food security and is determined by the level of food production, stock levels and net trade and all about having sufficient quantities of food from household production, other domestic output, commercial imports or food assistance and (WFP, 2012). However, global food availability does not ensure food security in a particular country because what is available in the world market may not necessarily be accessible by the poor people in other developing countries since the economies of these countries may not generate the foreign currency needed to purchase food from the competing world market (Sisay, 2012).

2.2.2. Food accessibility

Food access implies that people must be in a position to regularly acquire adequate quantities of food through purchase, home production, barter, gifts, borrowing or food aid and also having adequate resource to obtain appropriate foods for a nutritious diet, which depends on available income, distribution of income in the household and food prices (WFP, 2012).

What comes at the forefront for the emphasis given to the concept of access in the 1980‟s food security definition and literature is Sen‟s (1981) entitlement approach which states that “starvation is the characteristic of some people not having enough food to eat. It is not the characteristic of there being not enough food to eat”. Access to food is determined by entitlements to food. Stocks of assets, physical and human capital, common property resources access, and variety of state, community and household level contracts are routes to entitlements.

2.2.3. Food utilization

Food utilization which is commonly understood as the way the body gains various nutrients in

the food. Sufficient energy and nutrient intake by an individual are the result of good care and feeding practices, food preparation, and diversity of the diet and intra-household distribution of food. It entails cooking, storage and hygiene practices, health of individual, water and sanitations, feeding and sharing practices within the household. This determines the food insecurity of household members (WFP, 2012).

According to Klennert (2009), food utilization is proper biological use of food, requiring a diet with sufficient energy and essential nutrients, potable water and adequate sanitation, as well as knowledge of food storage, processing, basic nutrition and child care and illness management. This relates to the ability of the human body to take food and convert it. This gained energy is very important when it comes to daily physical activities, for example working in agriculture. Beside that utilization requires a healthy physical environment and adequate sanitary facilities as well as the understanding and awareness of proper health care, food preparation, and storage processes.

2.2.4. Stability

The last one is stability of the other three dimensions over time even if the food intake is adequate today. Stability describes the temporal dimension of food and nutrition security, respectively the time frame over which food and nutrition security is being considered (the ability to obtain food over time). Stability is given when the supply on household level remains constant during the year and in the long-term. That includes food, income and economic resources. Furthermore it is important to minimize external risks such as natural disaster and climate change, price volatility, conflicts or epidemics through activities and implementations improving the resilience of households. Such measure include insurances e.g. against drought and crop failure as well as the protection of the environment and the sustainable use of natural resources like land, soil and water ( Klennert, 2009).

The concept of food insecurity also has spatial and temporal dimensions. The spatial dimension refers to the degree of aggregation at which food insecurity is being considered. It is possible to analyze food insecurity at the global, continental, national, sub national, village, household or

individual level (Hoddinott, 1999).The temporal dimension refers to the time frame over which food insecurity is being considered. In much of the food insecurity literature, temporal dimension is almost universally classified into two states-chronic or transitory (Hoddinott, 1999; Tweeten, 1997).

Food insecurity can be transitory, seasonal, or chronic. In transitory food insecurity, food may be unavailable during certain periods of time. At the food production level, natural disasters and drought result in crop failure and decreased food availability. Civil conflicts can also decrease access to food. Instability in markets resulting in food-price spikes can cause transitory food insecurity. Other factors that can temporarily cause food insecurity are loss of employment or productivity, which can be caused by illness. Seasonal food insecurity can result from the regular pattern of growing seasons in food production. Chronic (or permanent) food insecurity is defined as the long-term, persistent lack of adequate food. In this case, households are constantly at risk of being unable to acquire food to meet the needs of all members. Chronic and transitory food insecurity are linked, since the reoccurrence of transitory food security can make households more vulnerable to chronic food insecurity (Ecker and Breisinger, 2012).

On the other hand, transitory food insecurity refers to a temporary decline in a household‟s access to enough food. It results from a temporary decline in a household access to food due to crop failure, animal diseases, seasonal scarcities, temporary illness, or unemployment, instability in food prices, production, household income or combination of these factors. But, the main triggers of transitory food insecurity in Ethiopia are drought and war (Devereux, 2010). Moreover, the cyclical type of food insecurity is caused by seasonality (Osmani, 2001). Since cyclical food insecurity generally follows a sequence of known events, it can be more easily predicted than transitory food insecurity. Hence, it can be categorized as a form of „recurrent transitory‟ food insecurity (Maxwell et al., 2008a).

2. 3. Food Security Indicators and Measurements

There are various approaches of estimating levels of household food security. However, there is no single approach, which is universally accepted as standard measure of food security. Global

household food insecurity level can be described by high food prices, high levels of malnutrition, high levels of maternal mortality, high levels of vulnerability and high levels of poverty. Vulnerability, for those concerned with food security, is the probability of an acute decline in food access or consumption due to hazards in the physical or social environment. Typical hazards include weather disturbances, such as drought or man-made disturbances, such as civil war or extreme price fluctuations (Clay, 2002).

Indicators are constructed from a set of observations or measurements of food security related conditions, which are classified according to a given set of criteria (Riely et al., 1999). A sound indicator needs to be relevant, low cost, time sensitive and adaptable across locations (Frongillo, 2004). It serves as a basis to periodically monitor food security and map vulnerability of a given situation, which in turn helps design a variety of interventions appropriate to the problem.

However, no identical indicator so far suffices to capture all aspects of food security. Indicators vary along the types and depth of investigations, procedures and level of aggregation.

According to Frankenberger (1992), the different types of indicators are classified into two broad categories; process and outcome indicators. The process indicators provide an estimate of food supply and food access situation; whereas an outcome indicator serves as proxies for food consumption. After making distinction between „‟process indicators‟‟ and “outcome indicators‟‟ explained each accordingly where process indicators were grouped in to indicators that reflect food supply such as meteorological data, information on natural resources, agricultural production data, food balance sheet and those reflect food access. On the other hand, outcome indicators can be grouped in to direct indicators, which are closest to actual food consumption, rather than indirect indicators focusing on storage estimates, subsistence potential ratio and nutritional status assessment.

Food security is measured at different level of aggregation and purpose. Three distinct levels of measurements including, national, household and individual levels are often applied in a given country. The measurement at national level is relatively more aggregated and mainly focuses on the food availability. At household level, the measurement takes different forms including food access and nutrition indicators. Some of these indicators show past food stresses that do not

serve as an instrument for current interventions. Nutritional outcome, for example, is the consequence of both inadequate food intake and poor absorption of food caused by environmental factors such as diseases and lack of health care (Frankenberger, 1992).

Measuring the required food for an active and healthy life and the degree of food security attained is a question to be addressed in a food security study. However, there is no single indicator for measuring it. Measurement is necessary at the outset of any development projects to identify food security, to assess the severity of food shortfall, and to characterize the nature of food security (Hoddinott, 2001).

Maxwell et al. (2008b) describe that the frequently available and utilized indicators which potentially measure food security as: nutritional status, actual food consumption at the household level by a 24-hour recall, coping strategies index, as well as proxy indicators such as calorie intake, household income, productive assets, food shortage, under 5 nutritional status, dietary diversity, and household food insecurity access scale. Although these indicators reasonably capture and designate a small portion of the problem, they do not provide a comprehensive picture.

There are four measures of household and individual food security: individual intakes, household caloric acquisition, dietary diversity, and coping indices (Hoddinott, 1999; 2002) these four common techniques are presented below:

Household caloric acquisition: It is a measure of the number of calories, or nutrients available for consumption by household members over a defined period of time. The principal person responsible for preparing meals is asked how much food was prepared for consumption from purchase, stock and/or gift/loan/wage over a period of time usually 7 or 14days (Bouis, 1993).

Individual intake: This is to undertake 24-hour recalls of food consumption for individual members of a household, and analyze each type of food mentioned for caloric content (and sometimes a more complete nutrient analysis). While this method results in more reliable consumption data and captures intra-household distributional differences, it is subject to a number of drawbacks: memory lapses, observer bias, respondent fatigue, a short and possibly

unrepresentative recall period, and such high data collection costs that resources often constrain analysis to relatively small samples (Bouis, 1993).

Coping strategies index: This is a simple method and requires less resource and time. It does not require skilled man power and can be handled by rapid appraisal techniques. The index is derived from household coping strategies and enables researchers to capture the state of vulnerability of food insecurity. The core technique is to organize and synthesize the information in to a comparable figure. It allows use of a single or a combination of many coping strategies to delineate secure and insecure households. The method may be applied in many ways, depending on the level of accuracy required and the type of data available (Hoddinott, 1999). According to the study of Maxwell et al. (2002) some disadvantages of this measure are: as it is a subjective measure, different people have different ideas as to what is meant by “eating smaller portions” comparison across households or a locality is problematic.

Dietary diversity: One or more persons within the household are asked about different items they have consumed in a specified period. Where it is suspected that there may be differences in food consumption among household members. The disadvantage of this measure is that the simple form of this measure doesn‟t record quantities. If it is not possible to ask about frequency of consumption of particular quantities, it is not possible to estimate the extent to which diets are inadequate in terms of caloric availability (Migotto et al., 2006).

For this study, household‟s calorie intake was used in order to measure household food security and to calculate the cutoff point (food insecurity line) beyond which a household is food secure or not. The reason for use of this measure was that it produces a crude estimate of the number of calorie available for consumption in the household. Moreover, Hoddinott (2001) mentioned that it is not obvious to respondents how they could manipulate their answers. Because the questions are retrospective, rather than prospective, the possibility that individuals or households will change their behavior as a consequence of being observed is lessened.

2.4. Empirical Evidences

Many empirical evidences in eastern Ethiopia argued that the majority of households were food secure. For example, Lemma and Wondimagegn (2014) revealed that the majority (62.7%) of households were food secure and about 37.3% were food insecure. Furthermore, Hussein and Janekarnkij (2013) pointed out that 63% of the households in Somali region were food secure, while 37% to be food insecure. As opposed to this, another study confirmed that about 56.5% of households in the area were food insecure (Abdirahman, 2015).

According to Misgana (2014) study conducted on rural household food security status and its determinant in the case of Laeleymaichew district, central zone of Tigray indicated that 31.2% and 68.8% sample households food secure and food insecure, respectively. In addition, the model result revealed total cultivated land holding size, total livestock holding, total annual income per AE and use of chemical fertilizer to positively related and statistically significant to food security status. In contrast, family size of the households negatively related and statistically significant to food security status of the rural households. Moreover, Furgasa and Degefa (2016) to assess household food security situation in central Oromia, Ethiopia used the household food balance model. The results indicated that high fertilizer price, shortage of farm land, erratic rainfall pattern, water logging, poor soil fertility, lack of oxen, lack of grazing land, crop disease and insect pests, lack of improved seed supply, and lack of farm machineries were identified to have mainly constraining food production among the study households.

Beyene and Muche (2010) pointed out that the majority of households in the central part of the country are food insecure (about 36% were food secure and the rest 64% of the households were food insecure). It also revealed that average value of the energy available for food secure and insecure households was 2,908 Kcal/AE/day and 1,822 Kcal/AE/day, respectively. The minimum and maximum energy available for food insecure households was 1,043 Kcal and 2,098 Kcal, respectively. Whereas the minimum and maximum energy intakes of food secure households were 2,203 Kcal and 3,492 Kcal, respectively. Furthermore, another study conveyed that 58.16 % of the total households in the area were food insecure with food insecurity gap and severity being 20 % and 9.4 %, respectively (Girma, 2012).

The study conducted by Fekede et al. (2016) using binary logit model found out that family size, livestock ownership, distance from market center, access to nonfarm activity and cash crop production were significant variables were identified to influence household food security positively. The econometric result revealed that the probability of being food secure increase with high livestock ownership, access to nonfarm activity and producing cash crops while large family size and far from market center reduce the probability of household to be food secure.

Amsalu et al. (2012) examined that the status and determinants of rural household‟s food security in Shashemene district of Oromia regional state, in Ethiopia. The headcount ratio, gap and severity of food insecurity were computed using FGT index and the result were 36, 12.38 and 7.35 percents, respectively. Logit model result also showed that factors such as, family size, cultivated land size, total farm income, off-farm income and livestock ownership of households were positively and significant influence household food security status.

The study conducted by Ehebhamen et al. (2017) using logistic regression model found that an increase in annual income, education, size of land cultivated, land ownership and livestock possession by the household‟s head affected food security positively and significantly. However, increases in age and household size to be negatively and significantly affected on food security status.

Different findings in the northern part of Ethiopia showed that there is high incidence of food insecurity. As to Mesfin (2014) finding, 48% of the households in the area were vulnerable to food insecure. In addition, the incidence of food insecurity in west and east Gojjam zones of Amhara region was 51.3% and 59.2%, respectively (Motbainor et al. 2016). A study conducted in drought prone areas of northern part of the country also indicated that the majority (74%) of households were experiencing food insecurity (Arega, 2013). Unlike to this, Tsegay (2009) figured out that the incidence of food security rural households in Tigray region was 42% which lower relative to other drought prone areas while 58% of rural households being food secure.

Several findings in the southern part of Ethiopia also showed that the incidence of food insecurity is lower relative to other parts of the country. As to Mitiku et al. (2012) finding,

about 64% of households in Shashemene district to be food secure while 36% were food insecure. In addition, Mequanent et al. (2014) revealed that 42.9% households were food insecure; whereas, 57.1% of them were food secure. Despite this, Nigatu (2011) depicted that about 54% of the households in some parts of southern Ethiopia have been facing mild to severe food insecurity. Ahmed (2015) also supported this by figuring out that about 77% of households in Bule Hora as food insecure households. Moreover, the majority (84.91%) of rural households in Guraghe zone were food insecure (Zelalem, 2014). A study conducted by (Buom, 2013) in Gambella region revealed that 80.8% of rural households were food insecure, whereas 19.2% of sampled rural household was food secure.

The logistic model result in rural Ethiopia indicated that improved food security is attained along with an increase in the size of cultivated land and livestock holdings. Off -farm and nonfarm incomes also influence the food security status of farm households. Their importance is significant in supplementing the total farm income and enhancing the state of household food security. Improved food security is observed as the intensity of fertilizer use increases (Fekadu and Mequanint, 2010).

2.5. Conceptual Framework

The food security status of a given country is determined by the interplay of natural, social and policy environments. The interplay of these factors also determines incomes and the food security at the household level (Ejigayehu and Edriss, 2012). There are four major elements of food security. They are food availability, food access, food utilization and not losing such access as it was mentioned in the conceptual definition previously. Availability, access and utilization are hierarchical in nature. Food availability is necessary but not sufficient for food accessibility and access is necessary but not sufficient for utilization (Webb et al., 2006).

In a larger sense, two broad groups of factors determine food security. These are supply the side factors and the demand side factors. The supply-side factors are determinants of physical access to food at household levels. The demand side factors are determinants of economic access to food items. Similarly, food availability in markets affects the prevailing prices (presuming the

price is not controlled) since urban and pre-urban households largely depends on market. A household with the necessary and sufficient purchasing power has access to food and can move in to the next higher stage that is utilization thereby become food secure. But, households who have no sufficient purchasing power due to low income and high market price can fall in to food insecurity (Ejigayehu and Edriss, 2012).

The final utilization of food by households besides the actual food intake is a function of access to safe water, health care and preparation. Food utilization comprises physical utilization and the biological utilization. The physical utilization is concerned with entitlement the physical means that can be consumed whereas the biological utilization is involved with the ability of the body to absorb nutrients from the food eaten effectively (WFP, 2009b).

Finally, good availability, sufficient purchasing power, good access and good utilization together determine household food security as it is depicted in the left part of figure 1. On the other hand, insufficient availability of food items from own production, stocks and aid and low purchasing power of the households due to low income and high price, less access to food items and in appropriate utilization of food ultimately bring food insecurity as it is shown in the right part of Figure 1. Then, food insecure household can be forced to adopt various coping strategies thereby it contributes to household food security.

Moreover, the arrows that directed towards food security indicate a good position in food availability, in purchasing power, in food access and in food utilization whereas the arrows that directed towards food insecurity indicate the poor food availability, low purchasing power, inadequate food access and inefficient food utilization. The above conceptual explanation is presented in Figure 1.

Food Security Coping Strategies

Food Utilization

Food insecurity Food Access

Purchasing power

Price

Income Food Market Availability

Natural Environment

 Production Social Policy  Stocks Environment Environment  Aid

Figure 1.Conceptual framework of the study Source: Adopted and modified from (WFP, 2009b)

3. RESEARCH METHODOLOGY

In this chapter, brief description of the study area, data types, sources and methods of data collection, sampling technique and sample size, methods of data analysis and definition of variables and hypothesis are presented.

3.1. Description of the Study Area

3.1.1. Location

The study was conducted in Oda Bultum District of West Hararghe Zone of Oromia National Regional State, Ethiopia. The total area of the district is 130,712 hectare and 1218 km2. Oda Bultum district is bordered on the south by Boke, on the west by Habro, then on the north by Chiro, on the east by Gemechis and on the northwest by Guba koricha. The district has 37 rural (Gandas) Kebeles and two towns, which are Karra and Burka. Badessa town serves as the main administrative center of district. Geographically the district is located between 8035‟00‟‟ and 9000‟00‟‟ North Latitude and 40033‟00” and 41020‟00” East longitude. The district also nearly elongates in its shape, it shares common zonal boundaries with East Hararghe zone (Gola Oda). The distance of district from the capital city of Ethiopia, Addis Ababa is 372 kms and 37 kms far from the capital city of zone, Chiro (OBDAO, 2018).

3.1.2. Population

According to OBDAO (2018) the total population of district was 216,746, of which 106,206 are men and 110,541 women. While 13,955 (6.4%) are urban inhabitants, a further 202,791(93.6%) are rural. A total of 45,156 households were counted in the district. The economically active (15-64) were 50% of the total population. Children below 15 years were 48%, while the elderly (65 years and above) were only 2%. The average household size in the district was five persons (CSA, 2015).

Figure 2: Geographic map of Oda Bultum district Source: GIS based own construction (2019)

3.1.3. Climate, land use and production activities

The temperature of the study area varies between 22°C -28°C with average 25°C and the annual average rain fall is around 1200 mm. The area has a subtropical (Weynadega), tropical (kola) and temperate (dega) type of climate division and accounting for 31%, 65% and 4% respectively. Physiographically, Sabale, Obii, and Sagariga mountain chains characterize Oda Bultum district. Attitudinally it extends between 1437 and 2500 meter above sea level (M.a.s.l). The households of the district held an average of 0.5 hectares of land. From total district area of land (130,712 hectare), 20,875 hectare was under cultivation,15,073 hectare was cultivable land

area, 15,714 hectare are not used (suitable) for cultivation, 9,524 hectare was under social use, 13,754 hectare used for pasture, 30,757 hectare was forest area (man made and natural) and 25,015 hectare covered by bush and shrubs. For the land under cultivation in this district, 82% is planted in cereals like maize and 18% left with others (OBDAO, 2018).

Mixed farming system (crop-livestock integration) prevails as dominant economic activity in the district. Depending on the agro ecological location (livelihood), households in the study area produce varying degree of mix of cereals, pulse, oil seed (groundnut) and livestock. Some household also grows cash crops such as coffee and vegetables to lesser extent with almost all households producing Jima/khat. Sorghum and maize were the two most dominant food crops (Ibid).

Crops and cropping activities are essentially determined by rain patterns; and rain distribution. The pattern of rainfall is bimodal in its distribution results two cropping season, locally named as the short rainy season Arfasa/Belg and whereas the long rainy season Ganna/kiremt. Livestock production is one of the major components of the farming systems in the study area as well and contributes to the subsistence requirement of the population, among other, in terms of milk and milk products and meat and draft power. Cattle and goats are the major livestock produced in the study area. Oda Bultum district is one of the food insecure districts, which the government has taken as a pilot district for the implementation of PSNP starting from 2005 up to now (Ibid).

3.2. Data Type, Sources and Methods of Data Collection

3.2.1. Data type and sources

Both qualitative and quantitative types of data were collected from primary and secondary sources. The required data was generated from both primary and secondary sources. To complement the primary data, secondary data was also generated from various sources, former conducted researches, official websites, unpublished documents, and publications of government offices such as regional/zonal/district agricultural offices.

3.2.2. Methods of data collection

Primary data was collected by using household survey via using structured questionnaire that was administered by trained enumerators who have knowledge about the area and well acquainted with the culture and language.

Household Survey: For the actual survey work, the survey instrument was translated in local language (Afan Oromo) because enumerators can communicate easily with the respondents. The data required for analyzing the household‟s food insecurity and coping strategies were gathered by incorporating the most important socio-demographic, economic profiles and characteristics of the categories of respondents.

The study used various secondary sources to augment the primary data. This constitutes written documents including those from agro-pastoral and sedentary farming rural development bureaus and recent research works which are related to the study and study areas. It includes review of relevant journals, books, conference proceedings, academic thesis and dissertations, reports from respective administrative layers, as well as reports of governmental and non-governmental organizations. Different offices and individuals were contacted to secure additional information.

3.3. Sampling Techniques and Sample Size Determination

A multi-stage sampling procedure was applied to select representative sample respondents. In the first stage, the Oda Bultum district was purposively selected, because the district is more prone to food insecurity problems. In the second stage, based on livelihood types, the (Gandas) Kebeles of the district were stratified into two strata: agro-pastoral (having 17 Gandas/Kebeles) and sedentary farming (having 20 Gandas/Kebeles). In the third stage, two (Gandas) Kebeles from agro pastoral namely Bososo and Haroreti and two from sedentary farming namely Kolu and Oda Baso were randomly selected. Finally, after having a list of total number of households in each (Ganda) Kebele, 365 households were selected by using simple random sampling with probability proportional to size: 172 households from agro-pastoral and 193 from sedentary farming households.

The desired number of sample household was determined by using a formula developed by Yamane (1967). To determine the required sample size at 95% confidence level, with a 0.5 degree of variability and 5% level of precision, the following formula was used.

N n 2 1N(e) (1) where, n is sample size, N is the number of household and e is the desired level of precision. As 4,185 households are living in the four sample Gandas/Kebeles.

4,185 n  2 1 4185(0.05) n = 365 households

Table 1: Total number of sampled HH heads

Gandas/Kebeles Livelihood Total household heads sample

Bososo Agro pastoral 1,230 107 Haroreti Agro pastoral 749 65 Kolu Sedentary farming 1,246 109 Oda baso Sedentary farming 960 84

Total 4,185 365

3.4. Methods of Data Analysis

Following the data collection, the data was coded and entered into statistical software called Statistical Package for Social Sciences (SPSS) version 20 and STATA for analysis. The household data was analyzed using both descriptive and econometric methods of analysis.

3.4.1. Descriptive analysis

To explain the demographic and socioeconomic situations of the households, the descriptive statistics like mean, variance, standard deviation, frequency distributions, ratios, and percentage were employed.

Measuring the Status, Prevalence and Severity of Household Food Insecurity

The households daily caloric intake per adult equivalent (calorie per AE per day) was calculated by dividing the households daily caloric intake by the household size after adjusting for adult equivalent using the consumption factor for age-sex categories (Zegeye, 2009). Then the results were compared with the minimum subsistence requirement per AE per day at 2,200 Kcal which is set by the Ethiopian Government (FSS, 2002). Hence, for this study 2,200 Kcal per adult equivalent (AE) per day was employed as a cut-off point between food secure and insecure households. Beyond which the household is said to be food secure and if below, food insecure.

The households‟ food security status was measured by direct survey of consumption. Household caloric acquisition is a measure of the number of calories, or nutrients available for consumption by household members over a defined period of time. The principal person responsible for preparing meals were asked how much food was prepared for consumption from purchase, stock and/or gift/loan/wage over a period of time. In this study, a seven day recall method was used since such a measure gives more reliable information than the household expenditure method (Bouis, 1993).

To estimate the status, prevalence and severity of household food insecurity in the study area the Foster Greer Thorbeke (FGT) index was used. This model provides the three most commonly employed indices namely head count ratio, food insecurity gap and severity. These indices show the different situation of food insecurity. The head count ratio indicates the number of households whose consumption is below the bench mark; in this study 2200 kcal/AE/day is the bench mark. Whereas, the food insecurity gap or depth measures how far the food insecure households are below the cut of value. On the other hand, squared food insecurity gap is more closely related to severity of food insecurity giving those further away from the minimum level by attaching a higher weight in aggregation than those closer to the subsistence level (Hoddinott, 2001).

Even though the model was widely used for poverty measurement studies; deferent researchers used the FGT index to determine the incidence and severity of food insecurity (Abebaw, 2003;

Aschalew, 2006). Consequently, to estimate head count ratio, food insecurity gap and to assess the severity of household food insecurity the Foster, Greer and Thorbecke (FGT) index was employed which was widely used for poverty measurement studies.

The model is expressed as follows:

 1 q Z _ yi FGT()    N i1  Z  (2)

Where, q = number of food insecure households, Z = minimum caloric intake, yi= is daily calorie intake per AE of ith households, α=weight attached to food insecurity which is α = 0 incidence/head count ratio, α =1 depth/gap and α = 2 severity of food insecurity and N = total sample size.

3.4.2. Econometric model

Choosing an appropriate model and analytical technique mainly depends on the type of dependent variable under investigation. Ordinary least squares method deals with cases where the dependent variable of interest is a continuous variable. But in many applications, the dependent variable of interest is not a continuous scale. It may have only two or more categories of limited possible outcomes.

Similarly, in this study, the dependent variable Y (household food security) is dichotomous variable taking value 1 if the household is food secure and 0 otherwise. In the case where the dependent variable is dichotomous, probability regression models are the most fitting to study the relationship between dependent and independent variables. In the case where the response variable is qualitative, it is the probability of the dependent variable given independent variable that is determined. The most common qualitative regression models are linear probability model, logit model, and probit model (Gujarati, 2004).

The Probit and Logit models are commonly used models when the dependent variable is binary. The Probit model is associated with the cumulative normal probability function, whereas, Logit model assumes cumulative logistic probability distribution. The advantage of these models over

the linear probability model is that the probabilities are bound between 0 and 1. Moreover, they best fit to the non-linear relationship between the probabilities and the independent variables; which is approaches zero at slower and slower rates as an independent variable (Xi) gets smaller and approaches one at slower and slower rates as Xi gets large (Train, 1986).

Linear probability model like a typical linear regression model, determine the conditional expectation of the dependent variable given independent variable. Beside this, the model is encountered with many problems like non-normality and heteroscedastic variances of the disturbance Ui and the probability fails to fall in between 0 and 1 values. For this reason, linear probability model is not attractive model and it is fallen out of use in many practical applications. These problems could be easily solved by using probit and logit models. In these two models the probability was fall in between 0 and 1. In most applications these two models are quite similar. The main difference being the logistic distribution has slightly fatter tails, that is to say, the conditional probability Pi approaches zero or one at a slower rate in logit than in probit. Therefore, there is no compelling reason to choose one over the other (Gujarati, 2004).

Probit analysis is a type of regression used to analyze binomial response variables. It transforms the sigmoid dose-response curve to a straight line that can then be analyzed by regression either through least squares or maximum likelihood. Probit analysis can be conducted by one of three techniques: using tables to estimate the probits and fitting the relationship by eye, hand calculating the probits, regression coefficient, and confidence intervals, or having a statistical package such as SPSS do it all for you.

Probit analysis is a specialized regression model of binomial response variables. Regression is a method of fitting a line to your data to compare the relationship of the response variable or dependent variable (Y) to the independent variable (X).

Yi xui (3) where

th Yi = food security status of the i respondent (household)

x = vector of determinants of food security

 = vector of parameters of interest

th ui = residuals of the i respondent of the household

A binomial response variable refers to a response variable with only two outcomes. The Probit Model assumes that the function F follows a normal (cumulative) distribution,

x F(x) (x)  (z)dz  (4)

Where (z) is the normal density function,

z2 exp( ) (z) 2 2 (5)

Therefore, in this study probit model was used over other alternative models because its interpretation is logical and clear to understand.

In this study, variance inflation factor (VIF) was used to detect the multicollinearity among the explanatory variables. In this method, each explanatory variable would be regressed on all other explanatory variables and coefficient of determination would be computed for each subsidiary regression. Following Gujarati (2004), VIF is specified as follows: 1 VIF(Xj)( ) 1 2 Rj (6) th 2 Where: Xj is the j explanatory variable, R j is the coefficient of determination when the variable Xj is regressed on the other explanatory variables.

Link test was used to test the specification of the dependent variable; it is often interpreted as a test that show whether the regression model is specified appropriately or not. Hosmer-Lemshow test were also used to test the goodness of fit of the model.

3.5. Definition of Variables and Working Hypotheses

3.5.1. Dependent variable

Household food security status (HFINS): It is a dichotomous dependent variable in the model taking a value 1 if the household is food secure and 0 otherwise. Household‟s food security status was determined by comparing total kilocalories consumed in household per adult equivalent per day with the daily minimum requirement of 2,200 kilocalories per adult equivalent per day. Households getting 2,200 Kcal/AE/day and above was considered as food secure and otherwise food insecure.

3.5.2. Independent variables

It is hypothesized that a household food security at any time is influenced by the combined effects of a number of factors. The independent variables that are expected to have association with the household food security were selected based on available literature. Any explanatory variable having negative coefficient was expected to reduce food security of the household whereas explanatory variable found to be positive were increased the food security of the households. Therefore, the major variables expected to have influence on the household food security were explained below:

Age of household head (AGEHH): It is a continuous explanatory variable referring to the age of the household head in years. Indris (2012) found out that age of a household head affected food insecurity positively. He argued that, as the age of a person gets older, the ability and strength of the person gets weaker so that there is more probability of that household to be food insecure (Ahmed, 2015). Thus, it is hypothesized that age of the household head and food security are negatively correlated.

Sex of the household head (SEXHH): It is a dummy explanatory variable taking a value of 1 if the household head is male and 0 otherwise. Greenwell and Pius (2012) stated that gender in Africa is much more related to access to resources. In Africa context, most females are resource poor which may contribute female headed households to be in food insecurity status than male

headed households. In this study, a male headed household is expected to be more food secured than their counter female headed households.

Educational status of the household head (EDUCHH): It is a continuous variable which is peculiar to the household head. It was measured in years of schooling for the household head. Egigayehu and Edriss (2012) indicated that households who have household heads with relatively better education are more likely to be food secure than those headed by uneducated (illiterate) household heads. So, education is expected to have a positive impact on food security.

Livestock ownership (excluding oxen and donkey) (LVTKOWN): It is a continuous variable measured by the number of Tropical Livestock Unit (TLU). Livestock are important source of food and income for rural households. Households with more livestock produce more milk, milk products and meat for direct consumption. Besides, livestock enable the farm households to have better chance to earn more income from selling livestock and livestock products which assist them to purchase stable food during food shortage and invest in purchasing of farm inputs that increase food production, and ensure household food security (Mitiku et al., 2012; Gemechu et al., 2015). Livestock possession mitigates vulnerability of households during crop failures and other calamities (Jemal and Kim, 2014). Thus, this study hypothesized that owning more livestock is expected to have positive effect on food security of households.

Number of oxen owned (NOXO): It refers the number of oxen possessed by the household. It is a continuous variable measured by number. Furgasa and Degefa (2016) found significant and positive relationship between number of oxen holding and household food security. Oxen are the most important means of land cultivation and basic factor of production in traditional agricultural practice. Households who own more oxen have better chance to escape food shortages since the possession of oxen allows effective utilization of the land and labor resources of the household. Thus, It allows the family labor to spread over peak and slack period to carry out both farm and non-farm activities. It is hypothesized that there is positive relationship between number of oxen holding and household food security.

Number of donkey owned (NODO): It is a continuous explanatory variable measured in numbers. Donkey serves as transportation in many developing countries, thereby significantly affecting household‟s livelihood activities. Animal power enables households to transport their production, firewood, charcoal and water to the market (to the place they need to transport) and also generate income by renting for others as a transport (Avornyo et al., 2015). Accordingly, in this study more donkeys owned by a household are expected to affect food security positively.

Total annual income excluding off/non-farm income (lnincome): It is a continuous variable which represents the total amount of annual income of household per adult equivalent in ETB from different source. Since, in the study area the main source of income for agro pastoralist is selling of livestock and some livestock products as well as crop and for sedentary farming is selling of crop product as well as cash crop. Studies revealed that the higher the income the higher the likelihood of the household becomes food secure (Titus and Adetokunbo, 2007; WFP, 2009a; Ejigayehu and Edriss, 2012). It is hypothesized that income of the household head positively relates with food security.

Size of cultivated land (SCULND): Total cultivated land owned by household is a continuous variable measured in hectare. Lewin and Fisher (2010) indicated in their study that size of cultivated land and food insecurity has negative relationship. Farmers who have larger farm landholding would have less probability to be food insecure (Zelalem, 2014). So that households with large cultivated land size are expected to produce more and those with small cultivated land is expected to produce less. Therefore, it is hypothesized that size of cultivated land and food security has positive relationship.

Off/non-farm income (OFRMI): Income earned from off/non-farm activities is continuous explanatory variable that was measured in birr. In this regard, households engaged in off/ non-farm activities are more endowed with additional income and more likely to be food secure. Fekede et al. (2016) found negative and significant relationship between off/non-farm income and food insecurity status of the household. Therefore, off/non-farm income was expected to be positively associated with household food security status.

Household size (HHS): It is a continuous variable which refers to the number of family size in a household in terms of adult equivalent (AE). Indris (2012) indicated that the higher the family size in adult equivalent, the higher would be the level of consumption which requires large quantity of food entailing positive relationship with food insecurity status. The reason is that households with large number of family members may face food insecurity because of high dependency burden created as a result of sharing available limited resources (Stephen and Samuel, 2013; Muche et al., 2014). Therefore, it is hypothesized that family size is negatively associated with food security of the households in the study area.

Number of livestock died in a year (NLVD): This variable is continuous and represents the number of livestock died or the number of animals lost as a result of various disease incidences measured in TLU. Indris (2012) found that prevalence of disease is one of the limiting factors in livestock production system of the agro pastoralists‟ society and has a significant impact in determining the agro pastoralist food insecurity status. Due to the limited supply of veterinary services and facilities in the study area, the existence of animal disease incidences deteriorated the livelihood of the agro pastoralists and signaled positive impact in aggravating food insecurity. Thus, negative relationship is expected between numbers of livestock dead in a year and food security.

Dependency ratio (DEPRATIO): Household members aged below 15 and above 64 are considered as dependent and dividing it by household members whose age is between 15-64 resulted in dependency ratio (Velasco, 2003). These groups are economically inactive and burden to the other member of household. Due to scarcity of resources, higher dependency ratio imposes burden on the active and inactive member of household to fulfill their immediate food demands (Muche et al., 2014). Besides, higher dependency ratio indicates that the labor force is small, with a constraint on the household per capita income and consumption, which also influences the wellbeing of the household members. It is hypothesized that dependence ratio and food security status of household are negatively related.

Distance from the market center (DISTMRKT): It is a continuous variable measured in kilometer. Proximity to market centers create access to additional income by providing

opportunities of selling livestock and livestock products as well as get opportunities of engaging in employment and easy access to inputs and transportation (Wali and penporn, 2013). It is therefore, expected that household nearer to market center have better chance to improve food security status than who do not have a proximity to market center. It is hypothesized that proximity to market center affects food security negatively.

Access to irrigation (ACTIRG): It is a dummy variable taking a value of 1 if the farmers have access to irrigation and 0, otherwise. Irrigation, as one of the technology options available, enables smallholder farmers to directly produce consumable food grains and/or diversify their cropping and supplement moisture deficiency in agriculture so that it helps to increase production and food consumption (Van der Veen and Tagel, 2011). Thus, in this study, it is expected to have positive impact on extent of households‟ food security.

Frequency of extension contact (FRECON): It is a continuous explanatory variable measured in number of visits by extension agent per year. More frequent extension contact enhances households‟ access to better crop production techniques, improved input as well as other production incentives, and this helps to improve food energy intake status of households (Hussein and Janekarnkij, 2013). Accordingly, in this study more number of extension contacts was expected to affect extent of households‟ food security positively.

Access to credit (ACTCRDT): It is a dummy variable, which takes the value of 1 if the household head had access to credit and 0 otherwise. Availability of credit eases the cash constraints and allows farmers to purchase inputs such as fertilizer, improved crop varieties, and irrigation facilities; which in turn enhance food production and ultimately increase household food energy intake (Stephen and Samuel, 2013). In this study, it is expected to affect extent of households‟ food security positively.

Types of farming activities (TOFA): This is a dummy variable that takes a value of 1 if a household head is engaged in sedentary farming and 0, otherwise (agro-pastoralist). The households who perform sedentary farm activities are better than the households of agro-pastoralist (Muwanga et al., 2020; Goswami et al., 2014). Therefore, in this study,

sedentary farming is expected to have positive relationship with household food security, which implies that the food security increases with sedentary farming.

Cash crop production (CASHCP): It is a dummy variable that takes a value of 1 if the household has produces cash crops and 0 otherwise. Households who produce cash crops are in a better position than those who did not produce cash crops (Fekede et al., 2016). Therefore, in this study, cash crop production is hypothesized to have positive relationship with household food security, which implies that the food security increases with producing cash crop.

Membership to agricultural cooperatives (MEMACOP): It is a dummy variable that takes a value 1 if a household is a membership to agricultural cooperatives and 0, otherwise. Musa and Hiwot (2017) indicated that agricultural cooperatives are effective in improving the wellbeing of the rural community. Agricultural cooperative members have significantly higher consumption per adult equivalent than nonmembers and individuals who are not a member of agricultural cooperatives have lower consumption per adult equivalent than a member of agricultural cooperatives. In this study, it is expected to affect extent of households‟ food security positively.

Table 2: Summary of definition of variables and hypothesis

No. Independent Variables Types-Var Unit of measurement Expected sign

1 Age of household head Continuous Years - 2 Sex of the household head Dummy 1 for male,0 for female + 3 Educational status of household Dummy Years of schooling + 4 Livestock ownership Continuous TLU + 5 Number of Oxen Continuous Number + 6 Number of Donkey Continuous Number + 7 Size of cultivated land Continuous Ha + 8 Off/non-farm income Continuous ETB + 9 Household size Continuous AE - 10 Number of Livestock died in a yr Continuous TLU - 11 Dependency ratio Continuous Number -

12 Distance from market center Continuous Km - 13 Access to irrigation Dummy 1if access,0 if not + 14 Frequency of extension contact Continuous Number + 15 Access to credit Dummy 1 if access,0 if not + 16 Types of farming activities Dummy 1for sedentary farming, + 0 for agro-pastoral 17 Cash crop production Dummy 1if HH produce, + 0 if not produce 18 Total annual income Continuous ETB + 19 Membership to cooperative Dummy 1 for member, 0 if not +

Source: literature reviewed (2019)

4. RESULTS AND DISCUSSIONS

This chapter presents the results of the study pertaining to various objectives. Descriptive results are discussed in section 4.1, 4.2, 4.3; Section 4.4 presents and discusses the econometric model results.

4.1. Household Food Security Status

The result from the sampled 365 respondents indicated that 142 (38.9%) and 223 (61.1%) of the households of the study area were food secure and insecure, respectively. The maximum and minimum kilocalories consumed by a single adult in a day for food secure households were 3265.065 and 2206.087 kcals, and 2198.87 and 1561 kcals for food insecure households.

The mean calorie intakes by food secure and food insecure sampled households were 2488.49 kcals and 2008.3 kcals. The difference is significant at 1% significance level. The standard deviations for food secure and food insecure households were to be 193.24 and 133.23 respectively (Table 3).

The mean daily calorie intake per day per AE was 2195.11 kcal which is below the national average of daily requirement of 2200 kcal per day per adult equivalent for active and healthy life.

Table 3: Mean differences test of daily calorie intake by food security status

Daily Energy Available per Food secure Food insecure Total sample t-value AE in (Kcal) (N=142) (N=223) (N=365)

Maximum 3265.065 2198.87 3265.065 Minimum 2206.087 1561.00 1561.00 -28.08*** Mean 2488.49 2008.3 2195.11 Standard deviation 193.24 133.23 283.3

Source: Own computation results based on survey data, 2020. Note: *, ** and *** show significance levels at 10%, 5% and 1%, respectively.

Food security status of household in the study area was 53% (101) of sedentary farming and 24% (41) of agro-pastoral were food secure respectively and while 76% (131) and 47% (92) of food insecure households were from agro-pastoral and sedentary farming respectively.

80 76% 70

60 53% 50 47% 40 Agro-pastoral 30 24% 20 Sedentary 10 0 Food secure Food insecure

Food security status

Figure 3: Food security status Source: Own computation results based on survey data, 2020.

4.2. Incidence, Gap and Severity of Food Insecurity

This section presents the food insecurity indices measured in this study; namely, head count ratio, food insecurity gap and severity of food insecurity:

Incidence (Head count ratio): This finding indicated that out of 172 agro pastoral sample households 76% (131 households) were food insecure and out of 193 sedentary farming sample households 47% (92 households) were also food insecure. This result showed that agro pastoral households more food insecure than sedentary farming households in the study area. Overall 61.1% of the sampled households consume less than the minimum calorie requirement (2200 Kcal).

Food insecurity gap: It measures the mean depth of food insecurity among the food insecure households by which the food security status of the food insecure households falls below the minimum level of calorie requirement. Food insecurity gap provides the possibility to estimate resources required to eliminate food insecurity through proper targeting. The result indicated that the food insecure household from the agro-pastoral requires 7.5% (165 kcal per adult equivalent per day) and also the sedentary farming household requires 3.3% (72.6 kcal per adult equivalent per day). The overall calculated value for food insecurity gap was found to be 0.053. This implies that, each food insecure household requires on average 5.3% (116.6 kcal per adult equivalent per day) of the daily-recommended calorie to be food secured.

Severity of food insecurity: To address the most food insecure part of the sample households, severity of food insecurity was calculated. The result indicated that the inequality among food insecure households from agro-pastoral were 0.0104 (1.04%) and the inequality among the food insecure household from the sedentary farming were also 0.037 (3.7%). The overall survey result revealed that inequality among food insecure households were about 0.0069 (0.69%) in the study area, implying that there was no much difference between food insecure households daily calorie intake.

Table 4: Incidence, gap and severity of food insecurity

FGT Indices

Household-group Incidence Gap Severity (Livelihood)

Agro-pastoral 0.76 0.075 0.0104

Sedentary 0.47 0.033 0.0037

0.611 0.053 0.0069 Source: Own computation results based on survey data, 2020.

4.3. Descriptive Statistics

4.3.1. Descriptive statistics of continuous variables

The different characteristics of sample households were compared to see if there are significant differences between food secure and food insecure groups. These include, age of the household head, household size, educational level household, oxen holding, donkey holding, livestock holding, number of livestock died, off/non-farm income, total annual income, size of cultivated land, dependency ratio, distance from market and frequency of extension contact .

Education level of household head: The mean educational level of the sampled household heads was 1.27 with a standard deviation of 1.99. The minimum and maximum educational levels were 0 and 9. The mean educational level of the household heads was 2.11 (SD=1.98) and 0.74 (SD=1.8) for food secure and food insecure households, respectively. The statistical test of the mean educational level of the household heads shows that there was statistically significant difference between food secure and food insecure households at 1% probability level (Table 5). This showed that food secure households had achieved more grade level than food insecure households which may help them to reduce the risks of food insecurity.

Livestock ownership: The livestock ownership per household measured in TLU for the sampled households varies from a minimum of 0.00 to a maximum of 13.54. Average livestock ownership of the sampled households was 4.14 with a standard deviation of 2.82. The average livestock ownership was 3.70 with the standard deviation of 2.96 for food secure and 4.42 with the standard deviation of 2.69 for food insecure households, respectively. Therefore, the mean livestock ownership by food secure households was significantly higher than the food insecure and the difference was significant at 5% significance level (Table 5).

Donkey ownership: The average number of donkey for the sampled households was 0.45 with the standard deviation of 0.63. For food secure households, the average number of donkey owned was 0.63 with the standard deviation of 0.72. Whereas for food insecure households the average number of donkey owned was 0.33 with the standard deviation of 0.53. The average numbers of donkey owned appeared greater for food secure households as compared to food

insecure households and this difference was statistically significant at 1% significant level (Table 5).

Size of cultivated land: The cultivated land per household for the sampled households varies from a minimum of 0.25 ha to a maximum of 3 ha. Average cultivated land of the sampled households was 0.86 ha with a standard deviation of 0.45. The average cultivated land was 0.91 ha with the standard deviation of 0.50 for food secure and 0.82 ha with the standard deviation of 0.41 for food insecure households, respectively. Therefore, the mean cultivated land by food secure households was significantly higher than the food insecure and significant at 10% probability level (Table 5).

Total annual income: The mean annual income per adult equivalent of the sampled household heads was 18988.04 with a standard deviation of 4067.3. The minimum and maximum annual incomes were 8500 and 35500 birr. The mean annual income of the household heads was 22806.02 (SD=3350.8) and 16556.9 (SD=2175.4) for food secure and food insecure households respectively. The statistical test of the mean annual income of the household heads shows that there was statistically significant difference between food secure and food insecure households at 1% probability level (Table 5). This showed that food secure households had achieved more annual income than food insecure households which may help them to reduce the risks of food insecurity.

Number of livestock died in a year: The number of livestock died in a year per household for the sampled households varies from a minimum of 0 to a maximum of 3. Average number of livestock died in a year of the sampled households was 0.33 with a standard deviation of 0.59. The average number of livestock died in a year was 0.26 with the standard deviation of 0.62 for food secure and 0.38 with the standard deviation of 0.57 for food insecure households, respectively. Therefore, the mean number of livestock died in a year by food secure households was significantly less than the food insecure. The difference was significant at 10% probability level (Table 5).

Dependency ratio (DR): The mean dependency ratio of the sample households was 0.85 with the standard deviation of 0.39. The minimum and the maximum dependency ratios were 0.00 and 2, respectively. The mean dependency ratio for food secure sampled households was 0.80 with the standard deviation of 0.41. For food insecure households, the mean dependency ratio was 0.88 with the standard deviation of 0.39. The mean dependency ratio of food insecure households was significantly higher than food secured households and the difference was significant at 10% significance level (Table 5).

Distance to nearest market: The distance from the market center of the sample households varies from the minimum of 2 to a maximum of 78. The mean distance of the sample households were 32.41 Km with the standard deviation of 30.86. The average distance from the market was 23.02 Km with the standard deviation of 29.45 for food secure and 38.39 Km with the standard deviation of 30.31 for food insecure households, this means, on average food secure households were travelling less distance than food insecure households. As a result, the differences of mean distance shows there was significant difference between the food secure and food insecure households in terms of the market distance at 1% significant level (Table 5).

Frequency of extension contact: The frequency of extension contact for the sampled households varies from a minimum of 0.00 to a maximum of 4. Average frequency of extension contact of the sampled households was 1.11 with a standard deviation of 1.10. The average frequency of extension contact was 2.03 with the standard deviation of 0.99 for food secure and 0.53 with the standard deviation of 0.70 for food insecure households, respectively. Therefore, the mean frequency of extension contact by food secure households was significantly higher than the food insecure. The difference was significant at 1% significance level (Table 5).

Table 5: Descriptive statistics of continuous variables Food-Secure Food-Insecure Total Sample (365) (142) (223) Variables Mean SD Mean SD Mean SD t-Value Age of household 48.74 7.68 49.18 8.41 49.01 8.13 0.51 Educational level 2.11 1.98 0.74 1.8 1.27 1.99 -6.84*** Livestock ownership 3.70 2.96 4.42 2.69 4.14 2.82 2.39**

Oxen Ownership 1.79 0.85 1.82 0.96 1.81 0.92 0.32 Donkey Ownership 0.63 0.72 0.33 0.53 0.45 0.63 -4.69*** Cultivated land 0.91 0.50 0.82 0.41 0.86 0.45 -1.69* Off/nonfarm income 3031. 1572.8 2876.2 1215.93 2936.8 1365.9 -1.06 9 Total income/AE 2280 3350.8 16556. 2175.4 18988. 4067.3 -21.6*** 6.02 9 04 Household size 4.79 1.45 5.06 1.69 4.95 1.61 1.56 Livestock died in yr 0.26 0.62 0.38 0.57 0.33 0.59 1.88* Dependency ratio 0.80 0.41 0.88 0.39 0.85 0.39 1.73* Distancefrom market 23.02 29.45 38.39 30.31 32.41 30.86 4.78*** Extension contact 2.03 0.99 0.53 0.70 1.11 1.10 -16.9*** Source: Own computation results based on survey data, 2020. Note: *, ** and *** show significance levels at 10%, 5% and 1%, respectively.

4.3.2. Descriptive statistics of categorical variables

The different characteristics of households like sex of the household head, cash crop production, access to irrigation, access to credit, types of farming and membership to agricultural cooperative were given due consideration.

Access to irrigation: The result obtained regarding access to irrigation shows that the users of irrigation accounted for 29.86 percent while non-users of irrigation accounted for 70.14 percent. The proportion of irrigation users was 11.66 percent of total sampled food insecure households. In addition to this; irrigation users accounted for about 58.45 percent of the total food secure households. Whereas, the proportion of non-users of irrigation out of total sampled food secure and food insecure households were 41.55 and 88.34 percent, respectively (Table 6). There was statistically significant proportion difference between food secure and food insecure households in terms of use of irrigation at 1% probability level.

Credit access: The result indicated that out of the sample households, access to credit use accounted for 36.71 percent while households which were not access to credit use accounted for 63.29 percent. The proportion of access to credit household heads was 32.74 percent of total sampled food insecure households. In addition to this; access to credit headed households accounted for about 42.96 percent of the total food secure households. Whereas, the proportion

of non-access to credit users household heads out of total sampled food secure households and food insecure households were 57.04 percent and 67.26 percent, respectively (Table 6). There was statistically significant proportion difference between food secure and food insecure households in terms of credit at 5% probability level.

Types of farming: The result indicated that out of the sample households 52.88% were from sedentary farming and 47.12% were from agro-pastoralist. Out of food secure households, 71.13% were from sedentary farming and 28.87% were from agro-pastoral. About 58.74% of the food insecure households were from agro-pastoral and the remaining 41.26% were from sedentary farming (Table 6). There was statistically significant proportion difference between food secure and food insecure households in terms of types of farming at 1% probability level.

Cash crop production: Out of the sample households 46.58% were cash crop producer and 53.42% were not cash crop producer. As expected, out of food secure households, 96.48% were cash crop producer and 3.52% were non-producer of cash crop. About 85.20% of the food insecure households were from non-producer of cash crop and the remaining 14.80% were from cash crop producer (Table 6). There was statistically significant proportion difference between food secure and food insecure households in terms of cash crop production at 1% probability level.

Membership to agricultural cooperative: Out of the sample households 42.47% were membership to agricultural cooperative and 57.53% were not membership to agricultural cooperative. About 82.4% of the food secure households were membership to agricultural cooperative and the remaining 17.6% were not membership to agricultural cooperative. Among food insecure households 82.96% from not membership to agricultural cooperative households and 17.04% were from membership to agricultural cooperative (Table 6). There was statistically significant proportion difference between food secure and food insecure households in terms of membership to agricultural cooperative at 1% probability level.

Table 6: Descriptive statistics of categorical variables Food secure (142) Food insecure (223) Total sample (365) Variable No % No % No %  2 -Value

Sex Male 89 62.68 121 54.26 210 57.53 2.52 Female 53 37.32 102 45.74 155 42.47 Irrigation Access 83 58.45 26 11.66 109 29.86 90.69*** Not access 59 41.55 197 88.34 256 70.14 Credit Access 61 42.96 73 32.74 134 36.71 3.90** Not access 81 57.04 150 67.26 231 63.29 Typeof farming Highland 101 71.13 92 41.26 193 52.88 31.07*** Lowland 41 28.87 131 58.74 172 47.12 Cash Crop Produce 137 96.48 33 14.80 170 46.58 232.62*** Not produce 5 3.52 190 85.20 195 53.42 Membership Member 117 82.4 38 17.04 155 42.47 151.7*** Not memb 25 17.6 185 82.96 210 57.53 Source: Own computation results based on survey data, 2020. Note: *, ** and *** show significance levels at 10%, 5% and 1%, respectively

4.4. Econometric Model Results and Discussions

4.4.1. Regression diagnostics

Prior to the estimation of the model parameters, detection and correction of multicollinearity and model specification were done. Variance inflation factor (VIF) was used to check multicollinearity problem between variables. Results of VIF showed that there was serious problem of multicollinearity among type of farming and lnincome of the explanatory variables, due to this reason the variable type of farming was excluded from the model because it was insignificant and replaced by agro-ecology (Appendix Table 4). The result of link test (pr>z = 0.935) indicated that the model is appropriately specified (Appendix Table 5).

4.4.2. Determinants of household food security status

Estimates of the parameters of the variables expected to determine the households‟ food security status were presented in Table 7. The goodness-of-fit was tested by the Log likelihood ratio (LR) test. The result showed that the chi-square value was 407.37 and the pro>chi2 was

0.000, this means that  2 is statistically significant and the model displays a good fit. The

Pseudo R2 of the model is also 0.84, implying that 84% of the variation in the model was explained by the independent variables. This verifies that the model has a good fit to the data and explained significant non-zero variations in factors influencing households‟ food security status.

Probit regression model was used to identify the determinants of households‟ food security status in the study area. Accordingly, variables hypothesized to have influence on the household‟s food security status in were fitted in the model. Therefore, out of 19 variables included in the model, nine (9) variables were statistically significant. Namely, sex of household head, educational level of the household head, donkey holding, off/non-farm income, household size, lnincome, access to irrigation, frequency of extension contacts and cash crop production.

Sex of household heads: It had significant and positive relationship with the household food security status. It was significant at 10 percent probability level. The result showed that male headed households were more food secure than female headed households. Other factors remaining constant, food security of male household headed increased by 12.5 percent than female headed households. The possible explanation was the differential access to production resources where male had more access to production resources like cultivated land than females. This result similar with the result of Greenwell and Pius (2012)

Educational level of household head: It had a positive and significant relationship with household food security at 5% significance level. Other variables remaining constant, an increase in the level of education by one year of school increases the probability that the household become food secure by 3.8 percent. That is, the more the educational levels of the household head, the higher the probability that the household become food secure (Table 7).

This finding is similar with the findings of Ehebhamen et al. (2017).

Donkey ownership: It had positive relationship with food security status and significant at 1% probability level. Other variables remaining constant, an increase in the number of donkey owned by one increases the probability that the household become food secure by 22.1 percent. The household who has more donkey they generate more income that increase food security, because donkey are used as the main transportation means, helped households to produce more by themselves or to earn income by renting their donkey to others which in turn helped households to access food in rural households (Table 7). This result is in line with the results of Avornyo et al. (2015).

Off/non-farm income: It had significant and positive relation with the food security status at 1% probability level and indicating that households engaged in off/non-farm activities have better chance to be food secure. This might be because households engaged in off/non-farm activities are more endowed with additional income and more likely to escape food insecurity. The marginal effect result shows that, a birr increase of income from off/non-farm activities, increasing the probability of households to be food secured by 0.01 percent. The explanation is that in this particular study, the household who solely depend on farm activities have inadequate income to purchase farm inputs and fulfill family needs and thus, they found to be food insecure. This shows that off-farm and /or non-farm job opportunities play prominent role in managing household food security in the district (Table 7). This finding is in line with the findings of Ahmed (2015).

Household size: It had significant and positive relationship with food security status at 1% probability level. The positive sign shows that the probability of becoming food secure is high for households where household size is high. Other variables remaining constant, as the household size increases by an AE, the probability that the household became food secure increases by 32.1 percent. The result is contradicted with the findings of (Stephen and Samuel, 2013; Indris, 2012; Muche et al., 2014). This is due to the reason of high active labor force in those families that have high family members.

Total annual income excluding off/non-farm income (lnincome): It had positive relationship with food security status and significant at 1% probability level. Other variables remaining constant, an increase in the income of the household by one birr the probability that the household become food secure increase by 142.3 percent. The household who have high income were more food secure than the households who have less income (Table 7). This result is in line with the results of (Ejigayehu and Edriss, 2012).

Access to irrigation: It had a significant influence and positive relationship with household food security at 5% probability level. This implies that the probability of being food secured households increases with access to irrigation. The marginal effect result show that, as compared to household who did not access to irrigation, the probability of the access to irrigation household‟s to become food secure was higher by 27.5 percent. Irrigation, as one of the technology options available, enables smallholder farmers to directly produce consumable food grains and/or diversify their cropping and supplement moisture deficiency in agriculture and helps to increase production and food consumption (Table 7). This finding is similar with the result of (Van der Veen and Tagel, 2011).

Frequency of extension contact: It had a significant and positive relationship with household food security at 5% probability level. This implies that the probability of being food secured households increases with access to frequency of extension contact. The marginal effect result show that, as compared to household who did not access to frequency of extension contact, the probability of the access to frequency of extension contact household‟s to become food secure was higher by 8.3 percent. More frequent extension contact enhances households‟ access to better crop production techniques, improved input as well as other production incentives, and this helps to improve food energy intake status of households (Table 7). This finding is in line with the result of (Hussein and Janekarnkij, 2013).

Cash crop production: It had a significant influence and positive relationship with household food security at 1% probability level. This implies that the probability of being food secured households increases with production of cash crop. Therefore, those households who produce cash crops being in a better position than those who did not produce cash crops. The marginal

effect result show that, as compared to household who did not produce cash crop, the probability of the cash crop producer household to become food secure was higher by 57.2 percent. Based on the above results, cash crop production is important in ensuring food security of the farm households (Table 7). This finding is similar with the findings of Fekede et al. (2016) and Nasir (2018).

Table 7: Determinants of food security status: Probit regression model Variable Coefficient Standard error Marginal effect Age of household head 0.015 0.027 0.003 Sex of the household 0.730* 0.397 0.125 Educational Level 0.209** 0.096 0.038 Livestock ownership -0.131 0.127 -0.024 Number of Oxen -0.149 0.285 -0.027 Number of Donkey 1.222*** 0.401 0.221 Size of cultivated land 1.053 0.763 0.191 Off/non-farm income 0.0004*** 0.0002 0.0001 Household size 1.771*** 0.497 0.321 Number of Livestock died in a 0.458 0.449 0.083 year Dependency ratio 0.50 0.52 0.091 Distance from market 0.0008 0.013 0.0002 Lnincome 7.856*** 2.054 1.423 Access to irrigation 1.164** 0.475 0.275 Frequency of extension 0.456** 0.255 0.083 contact Agro-ecology -1.571 1.21 -0.285 Access to credit -0.1099 0.348 -0.0195 Membership to Coop 0.308 0.447 0.058 Cash crop production 2.72*** 0.524 0.572 Constant -79.05 19.38

Log likelihood -40.25 Number of observations 365 LR chi2 (17) 407.37

Prob > chi2 0.000 Pseudo R2 0.84 Sensitivity1 0.81 Specificity2 0.68

Source: Own computation results based on survey data, 2020. Note: *, ** and *** show significance levels at 10%, 5% and 1%, respectively. 1. Correctly predicted food secure group based on 0.5 cut value 2. Correctly predicted food insecure group based on 0.5 cut value

The predicted Y hat [Y=Pr (HHFS=1)] was 0.104, suggesting that the success probability of being food secure by the sample households was about 10.4%.

The result of Hosmer-Lemeshow test (Prob>chi2 = 1.0000) indicated that the null hypothesis test of goodness of fit of the model was accepted. It suggested that the error term follows standard normal cumulative distribution function, thus the probit model was fitted for the data (Appendix Table 6).

5. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

This chapter has two sections. The first section deals with summary of the major findings of the study. The second section deals with conclusions and recommendations forwarded based on the study results.

5.1. Summary

This study was conducted in Oda Bultum district of West Hararghe zone of Oromia National Regional State with the specific objectives of to estimate the status, prevalence and severity of household food insecurity, determine factors that influence household food security level and identify the coping mechanisms adopted by households in the study area. To achieve these objectives, the study relied more on primary data, which were collected from 365 randomly selected households from four randomly selected kebeles of the district.

The data were collected on household demographic, economic, physical and institutional factors hypothesized to affect food security status of the households and were analyzed using descriptive statistics, FGT indexes and econometric method. The descriptive statistics were used to study the demographic, economic, physical and institutional factors in relation to food security status of the households.

The households of the study area were classified into food secure and food insecure groups based on kilocalories (kcal) consumed by the households during the previous seven days of survey data. Total amount of food commodity consumed by each household during the seven days was converted into equivalent daily (kcal) per adult equivalent (AE) and then compared with daily kcal recommended. Accordingly, 61.1% of sample households were living on total daily food energy level per adult equivalent of less than 2200 kcal (the minimum recommended requirement), while remaining 38.9% of sampled households were living on total daily food energy level per adult equivalent of greater than 2200 kcal (the minimum recommended requirement).

Binary probit model was used to analyze the determinants of households‟ food security status. The model result revealed that out of eighteen (19) variables included in the model nine (9) had significant effect on household food security status. Sex of household head, educational level of household head, donkey holding, household size, lnincome, off/non-farm activities, access to irrigation, frequency of extension contacts and producing cash crops are found to be positively and significantly determined household‟s food security status.

5.2. Conclusions and Recommendations

Study area is considered as food insecure district by the government; in line with this, the result of the study shows that 61.1% of the surveyed households were unable to get the minimum daily energy requirement.

Sex of household head had positive and significant effect on food security status. This means the probability of being food secure was high for male headed households. Therefore, in order to increase the food security status of households in the study area priority should be given to female headed households. Furthermore, strengthening capacity of females through education should be an integral part of the involvement.

Education level of household head showed positive and significant effect on food security status of the households. The education of household head could lead to awareness of the possible benefits of making agriculture a modern enterprise through advanced technological inputs, enhancing farmers to follow instructions on fertilizer packs and shall be used to diversification of household incomes that, in turn, would enable household food supply appropriately, due to this the government and concerned NGO need to work on the improvement of educational status of households especially the formal education.

Donkey ownership was the significant determinant and positively related with households food security. Donkeys are critical for food security due to its integral part related with transportation. Household having enough number of donkeys is more food secure than the one has no donkey. Moreover, it was observed from the field survey that as coping mechanisms, rural households sell their donkey during hard times to survive. Losing donkey made them very

difficult to recover even during the normal seasons. This forces household to be food insecure in the next unpromising season since they miss their integral part related with transport and income generate by renting their donkey to others. Due to this reason households should be supported to have donkey by enhancing income to overcome the household‟s capital problem, there have to donkey restocking program for households who lost their donkey from drought or any other shock.

Off/ non-farm activities are found to be positively and significantly influence food security status of the households. Because of it is crucial for expansion of the sources of farm house-holds‟ livelihoods. In this, case modern of production by providing the households with an opportunity to use the required inputs. It also minimizes the danger of food shortage during the time of unanticipated crops failure through food purchases. As a result, a great chance of famishment (a state of extreme hunger resulting from lack of essential nutrients over a prolonged period) for themselves and their families during periods of chronic or transitory food insecurity has avoided and reduced largely. In this regard, promoting off/non- farm activities can help rural households in solving capital problem, farm inputs, use for trade, etc. Hence, this calls for enhancing and expanding the off/non-farm activities for the farm households in the study areas, and this should be one of the areas of intervention and policy option.

Household size showed positive and significant influence on food security status. The higher family size has more contribution of income for the family which can improve the consumption of family by increasing the production or income generation via multi- direction. Thus, a positive relation between the household size and food security status, due to this reason the concerned body including the government should work on creating awareness for the family has many members relating with active labor force.

Cash crop production found to have a significant influence and positive relationship with household food security. Therefore, those households who produce cash crops being in a better position than those who did not produce cash crops. Because, cash crop production is important to ensuring food security of the rural households, thus concerning sectors of government as well as NGOs has to focus on its improvement.

Income of household head had positive and significant effect on food security status. This means the probability of being food secure was high for households have high income. Therefore, in order to increase the food security status of households in the study area, the government, NGOs and other concerned bodies should give the priority and work on the issue (activities) that can generate more income than before.

Access to irrigation found to have a significant influence and positive relationship with household food security status. This implies that the households who access to irrigation being food secured than households did not access to irrigation. Irrigation, as one of the technology options available, enables smallholder farmers to directly produce consumable food grains and/or diversify their cropping and supplement moisture deficiency in agriculture and helps to increase production and food consumption. Due to this reason the government and different NGOs should support rural households to access irrigation, especially by providing (outing) undergrounding water that can community used for irrigation all season.

Frequency of extension contact found to have a significant and positive relationship with household food security status. The food security of households increases with access to frequency of extension contact. The household who get access to frequency of extension contact better food secure than who did not get. More frequent extension contact enhances households‟ access to better crop production techniques, improved input as well as other production incentives, and this helps to improve food energy intake status of households, so the government should hire skilled and enough development agent to increase frequency of extension contact and awareness for rural households.

6. REFERENCES

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7. APPENDICES

Appendix 1: Conversion factors used to compute AE

Age group (years) Male Female

<10 years 0.6 0.6 10-13 0.9 0.8 14-16 1.0 0.75 17-50 1.0 0.75 >50 1.0 0.75

Source: WHO and FAO (1985).

Appendix 2: Conversion factors used to compute TLU

Animal Category TLU

Calf 0.50 Donkey (young) 0.35 Weaned Calf 0.34 Sheep and goat (adult) 0.13 Heifer 0.75 Sheep and goat (young) 0.06 Cow 1.00 Chickens 0.013 Ox 1.00 Donkey (adult) 0.70

Source: FAO (2004)

Appendix 3: Conversion factors used to estimate Kcal of food items

Food item Unit Kcal Barley Kg 3723 Maize Kg 3751 Sorghum Kg 3850 Wheat Kg 3623

Lentils Kg 3522 Onion Kg 713 Pepper Kg 933 Milk Lt 737 Sugar Kg 3850 Edible oil Lt 8964 Coffee Kg 1103 Peas Kg 3553 Tomato Kg 216 Salt Kg 1700 Rice Kg 3330 Meat Kg 1148 Butter Kg 7364 Spaghetti/Macaroni Kg 3550 Broad Bean Kg 3514 Cheek Peas Kg 3630 Egg Number 61.0 Spices Kg 2970 Garlic Kg 118 Sweet Potato Kg 1360 Irish Potato Kg 1037 Honey Kg 3605 Teff Kg 3589 Beef Kg 1148 Millet Kg 3260 Source: EHNRI, 1997

Appendix 4: Multicollinearity test

Variable VIF 1/VIF

TOFA 15.35 0.065148 LNINCOM 10.12 0.098814 DISTMRKT 8.61 0.116171 HHS 8.56 0.116868 LVTKOWN 5.93 0.168493 SCULND 3.58 0.279407 FRECON 2.86 0.349540 NOXO 2.68 0.373384 MEMTACOP 2.33 0.429843

CASHCP 2.12 0.472454 ACTIRG 2.09 0.477993 NLVD 1.77 0.563807 NODO 1.76 0.568383 EDUCHH 1.51 0.661703 AGEHH 1.45 0.688575 OFRMI 1.27 0.784991 SEXHH 1.14 0.874157 ACTCRDT 1.06 0.943981

Mean VIF 3.97

Source: Model output, 2020 Appendix 5: Link test of model specification Ho: The model is correctly specified

HHFS Coef. Std. Err Z P>ǀZǀ [95% Conf. Interval] hat 1.000282 0.1424831 7.02 0.000 0.7210199 1.279544 hatsq 0.0077225 0.0944025 0.08 0.935 -0.177303 0.1927479 cons -0.0095491 0.1968133 -0.05 0.961 -0.3952962 0.37161979

Source: Model output, 2020 Appendix 6: Hosmer-Lemeshow test Probit model for HHFS, goodness-of-fit test Ho: The error follows normal cumulative distributions

Number of observations 365 Number of covariate patterns 365 Pearson chi2 (345) 88.93 Prob > chi2 1.0000

Source: Model output, 2020

HARAMAYA UNIVERSITY

Food Security Status and Its Determinants among Rural Households: The

Case of Oda Bultum District, West Hararghe Zone, Oromia National

Regional State, Ethiopia

HOUSEHOLD SURVEY QUESTIONNAIRE

SECTION GI: GENERAL INFORMATION

1. Questionnaire No: ______Date of interview:______Start time:______End Time:______2. Name of Ganda/kebele: ______village: ______

3. Name of Household Head: ______Total family:______4. Household Code No: ______

5. For how long have you lived in this village? Age:______6. Livelihood: 1) Sedentary farming 0) Agro pastoralist

SECTION HR: DEMOGRAPHIC AND SOCIAL CHARACTERISTICS OF THE HOUSEHOLD

Household Roster Enter the HR02 HR03 HR04 HR05 HR6 HR7 names What is Educational Can read starting What is the Sex Age (years) marital level and with the relationship 1 Status? write? household to the Male 00if <1year 0.Less than head. household 2Fem 1 Married grade one 1=Yes head? ale 2 Separated 1.Grade 1 2 =No 01 Head or divorced 2.Grade 2 02 Spouse 3 Single 3.Grade 3 03 Child 4 Widowed 4.Grade 4 04 Other___ 5 Other___ 5. Grade 5 6.Grade 6 HR01 HR01 person of ID 7. Grade 7 8.Grade 8 9.Grade 9 10.Grade10

11.Others__ 1 2 3 4 5 6 7 8 9 10

SECTION LI: LIVESTOCK OWNERSHIP

LI1. Do you have livestock? 1. Yes 0. No If yes, fill the following table

(a) (b) (c)

Ownership of Number Average How has the What are the livestock of price in number of reasons for the animals (Birr) livestock owned by decrease in the last owned your household year?

changed during the (If response to (b) last year? is 1) 1 Decreased 1 Sold for food

Animal # Animal 2Remained the 2 Disease same 3 Died in drought

3 Increased 4 Others______LI01 Camels: Female LI02 Camels: Male LI03 Camels:YoungFemale LI04 Camels: Young Male LI05 Camels: under 1 year LI06 Cattle: Male bulls LI07 Cattle: Mature Male LI08 Cattle: Female LI09 Cattle: Under 1 year LI10 Goats LI11 Sheep LI12 Donkeys LI13 Mules LI14 Horses LI15 Poultry LI16 Bee keeping

LI17 How is the access to Regularly available 1 pasture for animals? Occasionally 2 Seldom available 3 Never available 4 LI18 How is the quality of Excellent 1 pasture for animals? Good 2 Adequate 3 Poor 4 Very poor 5 LI19 What are the three most ___,1st most problematic month problematic months for ___,2nd most problematic month pasture availability? ___,3rd most problematic month (Use Ethiopian month) LI20 How is the availability of Regularly available 1 water for animals? Occasionally 2 Seldom available 3 Never available 4

LI21 What are the three most ___,1st most problematic month problematic months for ___,2nd most problematic month water availability? ___,3rd most problematic month (Use Ethiopian month) LI22 During dry season, what River, Stream, Open/Deep well 1 is the main source of Pond or lake (open access) 2 water for livestock? Pond or lake (fenced) 3 Rainwater harvesting 4 Other______5 LI23 How much does it cost ______/______/______/ birr you to get water per week during dry season? LI24 During wet season, what River, Stream, Open/Deep well 1 is the main source of Pond or lake (open access) 2 water for livestock? Pond or lake (fenced) 3 Rainwater harvesting 4 Other______5

LI25 How much does it ______/______/______/ cost you per week birr during wet season? LI26 What are the diseases Anthrax affecting 1 ____,1st Most important that your livestock cattle/Aba sanga have suffered in the Black leg/Aba gorba 2 ____,2nd Most important last 5 years? Faciolosis/Ramo tiru 3 (Mark 3 most Foot and mouth diseases 4 ____,3rd Most important important that apply) Skin diseases 5 Pasteurellosis/Gororsa 6 Sheep box 7 Born diseases 8 Others______9

LI28 How is the access to Excellent 1 veterinary services? Good 2 Adequate 3 Poor 4 Very poor 5 LI29 How is the access to Excellent 1 drugs for livestock? Good 2 Adequate 3 Poor 4 Very poor 5 LI30 How many number of ______Mai ______

your livestock died in n this year? reas on of deat h?

SECTION LA: LIVELIHOOD ACTIVITY

LA01 Firewood LA08 Rearing and selling LA15 Traditional healer animals LA02 Charcoal LA09 Selling dairy products LA16 Daily labourer (e.g. milk) LA03 Water LA10 Selling eggs (from own LA17 Agricultural labourer chickens) LA04 Precious LA11 Selling cereal food crops LA18 Animal herder stones LA05 Wild LA12 Selling fruits (e.g. mango, LA19 Construction worker fruits papaya) LA06 Animal LA13 Selling vegetables LA20 Making traditional farm tools feed LA07 Buying LA14 Selling khat/chat LA21 Others______and Selling livestock

SECTION HF: SOURCES OF FOOD AND FOOD CONSUMPTION Sources of food HF01 What are the main sources of food 1 Own production for the HH in the last years? 2 Purchase 3 From family/Relative/Neighbors 4 PSNP/Food aid 5 Loan 6 Others______

HF02 Is the main sources of food are 1 Yes enough? 0 No HF03 For how many months your food 1 All round the year production is sufficient for you? 2 9-12 months 3 6-9 month, 4 3-6 month 5 <3 month HF04 If your answer is No for HF02, 1 June_ September which month of the year is food 2 October _January insufficient? 3 February _May

HF05 If there were a food shortage, what 1 Drought are the main reasons? 2 Lack of Oxen 3 Crop Damage due to pest and diseases 4 Land shortage 5 Excess rain 6 Others______

FOOD CONSUMPTION Over the last one week, how Did you How many Source of food many days did you consume the consume days during 1Own cultivation/Production following food items? the last seven 2 Casual labor 3 Borrowed following days did you 4Giftsfrom friends/neighbors items? consume the 5Purchase from shop 1 Yes following? 6 Food assistance 2 No 7Begging 8 Others______HF06 Bidena/Injera 1 2 HF07 Other cereals (Sorghum, 1 Maize, Millet, Wheat, 2 rice, bread etc.) HF08 Potatoes 1 2 HF09 Pasta, Biscuits 1 2 HF10 Sugar 1 2 HF11 Beans, lentils, nuts 1 2 HF12 Vegetables 1 2 HF13 Fruit 1 2 HF14 Milk 1 2 HF15 Meat 1 2 HF16 Oil/butter 1 2

HF17 Any Other (specify)____ 1 2

SECTION CC: CASH CROP PRODUCTION CC1. Do you have produce cash crops in your agricultural land? 1. Yes 0. No If yes, List the type of cash crops you cultivated and their average income

Type of cash crops Quantity (Kg) Annual Income (Birr) produce

Numbers CC01 CC02 CC03 CC04 CC05 CC06 CC07 CC08 CC09 CC10 Total

SECTION OF: OFF/NON-FARM INCOME OF1. Do you or any member of your family have off/non-farm job? 1. Yes 0. No If yes, indicate the type of work and annual income: NO. types of jobs Annual income

OF01 OF02 OF03 OF04 OF05 OF06 OF07

If payment were made in kind, convert them into birr at price prevailing at time.

1, Weaving/spinning, 2, Milling, 3, Other handcrafts (pottery, metal works, etc.), 4, Livestock trade, 5, Sale of local drinks 6, Agricultural employment, 7, Petty trade (grain, vegetables and

fruits), 8, Sell of firewood and grass, 9, Charcoaling, 10, Government employment, 11, Others (specify) ______What employment and income earning opportunities are available in your area? (You may choose more than one) 1, Only own farming (self-employment), 2, Own non-farm employment (trading crafts), 3, Farm laborer (work on other farms), 4, Migration to work in other areas, 5, Non-farm laborer (work in cities), 6, Other (specify) ______

SECTION AG: AGRICULTURE AND LAND USE INFORMATION

AG01 Does your Yes 1 household own No 2 land? AG02 How much ___/___/___/ hectares land does your Cultivated area ______household Grazing area______own? Forest land______Other______How did you Inherited/ gifts from 1 acquire your family 2 own land? Purchase 3 Land distribution 4 Other ______AG03 Did your Yes 1 AG05 household No 2 rent-out (including share-crop out) any plots of land in the last farming season? AG04 How much ____/____/______/ hectares land did your household rent-out last farming season (including share-crop out)? AG05 Did your Yes 1 AG26

household No 2 conduct crop farming activities in last 12 months? AG06 What is the ____/____/_____/ hectares size of own-land your households have cultivated last farming season? AG07 Did your Yes 1 AG09 household No 2 rent-in (including share-crop in) any plots of land in the last farming season? AG08 How much ____/___/____/ hectares If none, fill 00 land did your household rent in last farming season (including share crop in)? AG09 How much _____/____/____/ hectares land did your household cultivate last year? AG10 Do you have Yes 1 enough land No 2 for farming (given your household size and inputs available)? AG11 Is your farm Yes 1 situated in Partially 2 favorable site No 3

(e.g. at a valley bottom, near a water source, etc.)? AG12 What is the Highly fertile 1 nature of your Fertile 2 farm soil? Partially fertile 3 Not fertile 4 AG13 How do you Oxen 1 till your fields? Tractor 2 Manual 3 None 4 AG14 What is the River/Lake/Pond 1 source of Birkas (tanks) 2 irrigation in No irrigation (Rain-fed) 3 your farm? Other (specify)____ 4

AG15 Yes 1 Are you a No 2 membership of agricultural cooperatives? If your answer ______2 what is the _ reasons? AG16 What type of Chemical 1 Sources fertilizer do Natural/Animal manure 2 1 Cooperative you use? Both chemical and natural 3 2 Enterprise None 4 3 Other______If 4, what is the reason? 1 Too expensive 2 Not available 3 Other______AG17 What types of Chemicals (insecticides, 1 Pesticides do fungicide, etc) 2 you use? Natural methods None 3 Sources 1 Cooperative 2 Enterprise 3 Other______If 3, what is the reason? 1 Too expensive 2 Not available

3 Other______AG18 Do You use Yes 1 Sources improved No 2 1 Cooperative variety seeds? 2 Enterprise 3 Other______If 2, what is the reason? 1 Too expensive 2 Not available 3 Other______AG19 Does your Yes 1 household No 2 receive agricultural extension services? If 1, what Kind of ______extension service and for how many times? If 2, what is the reason? ______

List of Crops Cultivated in the last year AG20 AG21 AG22 AG23 AG24 AG25 AG26 Which Cultivated area Harvested Amou Percentage of Reason for

crop has (hectares) quantity in nt of damaged crop damage on

# your Kg output crop Irrigate Un-I

househol sold to 1.pests, Crop Crop d d rriga market insects, weeds cultivate ted in Kg 2. Drought

last year? 3 .Other_____ 1 2 3 4 5

CROP CODES

1 Teff 5 Sorghum 9 Peas 14 Linseed 19 Root 23 Chat 2 Barley 6 Millet 10 Lentils 15 Sunflower and tubers 24 3 Wheat 7 Beans 11 Other pulses 16 Sesame 20 Enset Other 4 Maize 8 Other grain 12 Neug 17 Other oil seed 21 Fruits cash (Specify)_____ 13 Groundnut 18 Vegetables 22 Coffee crop

SECTION MT: MARKETING MT01 Which market 1 Main market (s) does your 2 Local market household use? 3 Both MT02 What is average 1 Km______market distance 2 Hr______you travelled to 3 Minutes______the nearest market from your home measured in km or hr or minutes? MT03 Where do you 1 On farm. sell your farm 2 Local market produce? 3 Via cooperatives 4 Other ______MT04 What means of 1 Truck (vehicle) transport do you 2 Animal power use to transport 3 Human power 4 Others (specify) your production ______to the market?

MT05 When do you ______month sell most of your production? MT06 What are the ______reasons?

MT07 Did you get Yes 1 NO 2 reasonable price for your production at this particular time?

SECTION AC: ACCESS TO CREDIT AC01 Are you member of Yes 1 any credit/micro NO 2 finance society? AC02 Has any household Yes 1 member borrowed NO 2 any money in the If 1, when? ______last one year? AC03 How many times ______times did any household member try to borrow in the last one year? AC04 How many times ______times did the household member manage to get credit in the last one year? AC05 What were the Buy food 1 ____,1st Most important reasons for Pay for health care 2 ____,2nd Most important borrowing? Buy agricultural 3 ____,3rdMost important (List three main input 4 reason in order of Other importance) AC06 Where did you Relatives/Friends 1 ____,1st Most important borrow from? Neighbors 2 ____,2nd Most important (List three main Money lenders 3 ____,3rdMost important reason in order of Other______4

importance) AC07 Does any member Yes 1 of the household NO 2 have a bank If yes, would you account? tell me the amount ______of birr the account does have? Amount in Birr

If not, why?

AC08 If your household Yes, we use our 1 had a sudden need saving 2 for 500 birr would Yes, by borrowing 3 you be able to raise money 4 the money within a Yes, with some help 5 week? Yes, by selling asset 6 or livestock 7 Perhaps, but I doubt it NO, it would be impossible

SECTION HCE: HOUSEHOLD CONSUMPTION AND EXPENDITURE Household consumption during the last seven days (considering both home and outside of home situation) (Here, wife and/or the person involved in purchases and preparing the meal should be the principal respondent/s). HCE1. What portion of the rest of your annual life does last week‟s consumption represent? 1. One-fourth 2. One- half/average 3. Three-fourth 4. All-year-round 5. Double 6. Other______HCE2. During the days how many times do you eat the food? 1. One time 2. Two times 3. Three times HCE3. What types of food items used to your household consumption?

What food Food Source items were used Type Home Purchased Gift/Loan/ Total in Estimated for consumption produced Wage in number expenditure during the last kind in Birr seven days in Unit Quantity Qua Uni Source your household? ntity t

Did your Sorghum household Maize consume any Wheat cereals such as Barley Sorghum, Teff maize, wheat, Millet barley, millet, Rice etc? Did your Lentils household Beans consume any Chick pea pulses/legumes? Did your Cow milk household Cattle consume any meat animal product? Camel meat Goat meat Sheep meat Egg Butter

Did your Tea household Khat consume any Cigarettes khat, cigarettes, Soft tea or soft drinks drinks?