Project Topics
Get Complete Project Material File(s) Now! »
CHAPTER 4: RESEARCH DESIGN AND METHODOLOGY
INTRODUCTION
In assessing the factors affecting agricultural production in the study area, a mixed method research approach was adopted in which both qualitative and quantitative research techniques were used in the study. The type and source of data are explained. The dependent and independent variables of the models used in the study are properly explained and operationalized. The issues related to the target population and the sampling procedures of the study are explained in this section. The methods of data processing and analysis as well as the measures that have been taken to address the issues of validity and reliability are part of this chapter.
RESEARCH DESIGN
Research design provides a logical structure for research data gathering and analysis (Bryman, 2008, p. 31). The study adopted a cross-sectional survey research design as its framework to guide the process of data collection. According to Bryman (2008, p. 46), cross-sectional survey research design is the collection of data mainly using questionnaires or structured interviews to capture quantitative or qualitative data at a single point in time.
DATA TYPE
The focus of this study is to investigate the factors affecting agricultural production in the Tigray region, Northern Ethiopia. In addition, related issues such as agricultural marketing challenges and off-farm participation are part of the study. To this end, a mixed method research approach which involves the mixing of qualitative and quantitative research methods was used. The application of these combined research methods is vital for answering different types of research questions.
According to Henning, Van Rensburg & Smit (2004, p. 3), in a quantitative study, the focus is on the representation of subjects and the relationships between the different variables under consideration. On the other hand, the focus of qualitative research is not the issue of representation and quantification. In the processes of data collection and analysis, qualitative study gives due attention to words rather than quantification (Bryman, 2004, p. 266; Bryman, 2008, p. 366). The mixed methods research design creates a wider picture by enhancing the depth and insight given by numbers through inclusion of dialogue and narratives (O’Leary, 2010, p. 128).
The major factors affecting agricultural production are the household characteristics, technologies, credit markets, environmental (soil and climate) and rural infrastructure facilities (Endale, 2011, p. 23). In addition, the factors affecting agricultural production at the regional level are critically reviewed from the secondary sources. These factors are addressed using qualitative techniques. In order to assess the agricultural marketing challenges of farm households, a qualitative technique was also used. It is believed that agricultural production constraints and agricultural marketing challenges are addressed in a better way if they are explained using the words of the farm operators and other stakeholders. In relation to the agricultural production at the regional level, critical reviews of secondary sources, mainly from the Central Statistics Agency of Ethiopia and BoARD of the region were carried out. On the other hand, quantitative techniques are applied to variables such as the determinants of households’ farm, off-farm labour participation and off-farm income.
It is imperative to state the epistemological considerations about the acceptable knowledge in a discipline (Bryman, 2004, p. 11; Bryman, 2008, p. 13) or to identify the rules used for discovering what exists (O’Leary, 2010, p. 5). O’Leary adds that there are many and competing philosophical positions to understand our world and they influence the research processes. The Positivist framework is one of the competing philosophical positions. Positivism is a rejection of metaphysics and finding truth through empirical means (Henning et al., 2004, p. 17) and it is the epistemological position that utilizes the methods of the natural sciences to study social reality (Bryman, 2008, p. 13). On the other hand, interpretivism is an alternative to the positivist orthodoxy and it acknowledges that there is a difference between people and objects of natural sciences which requires the social scientist to understand the subjective meaning of social action (Bryman, 2008, p. 16).
As stated above, a mixed methods research design is one in which both qualitative and quantitative techniques are used in a single study. Researchers who used mixed research methods employ philosophical and methodological pragmatism (Onwuegbuzie, & Johnson, 2006, p. 54). For pragmatism, all human inquiry was related to experience and experience was active rather than passive and science opened new areas of experience for investigation (Heelan, & Schulkin, 1998, p. 272).
DATA SOURCES
The sources of data for the research are both primary and secondary sources. The major primary sources of data are structured questionnaires, focus group discussions and interviews as detailed below.
Structured survey questionnaire
Questionnaires were developed for responses fromthe selected rural household heads at the Kushet level (Appendix 1). The questionnaire was translated into the local language (Tigrigna). The questions were related to the agricultural production and marketing challenges, determinant factors for off-farm work and farm and off-farm income. The structured survey questionnaires were administered with the support of experienced research assistants. Each of the questions in the questionnaire was discussed with the research assistants before the field survey was started.
Focus group discussions
At the tabia3 level, focus group discussions were conducted with the selected rural households (Appendix 2). The focus group participants were selected purposely based on their knowledge and experience of the topic. This session included participants at the tabia level such as tabia administrators, elders, youth association leaders, rural trade and industry experts, credit and saving institute officers, micro enterprise owners and women’s association leaders. At the tabia level, three sets of focus group participants were involved. The plan was to take four groups of focus group participants from all tabias included in the study. However, because of the repetition of the information, two groups from Kilte Awlalo and one group from Ganta Afeshum district were utilized. In each of the sessions, eight to ten relevant individuals were included. Interviewees were not willing to be tape recorded due to the sensitivity of the topic. Hence, the reflections of farmers in the focus group discussion and interviews were captured by taking notes.
Interviews
At the tabia level, separate interviews with the extension agents were conducted. Taking two tabias from each selected district, the crop, irrigation, livestock and natural resource experts were interviewed (Appendix 3). Moreover, key informants from the regional bureau of agricultural and district level agricultural experts were interviewed (Appendix 4). The interviews were carried out after the preliminary results of the structured questionnaires. This arrangement helped the researcher to include more questions that needed further explanation.
Document analysis
In order to critically review the agricultural production at the regional level, secondary data sources were consulted. The Central Statistics Agency (CSA) documents were the main sources for reviewing agricultural production in Tigray. In addition, different publications and source documents such as rural development plans, regional development strategic plans and federal government documents were considered. Agricultural Development-Led Industrialization strategy (ADLI), Growth and Transformation Plans (GTP) of the federal and regional, Ministry of Agriculture and Rural Development, Bureau of Finance and Economic Development of Tigray, as well as Agricultural Marketing Support Agency were some of the relevant secondary sources institutions. Internet and previous studies worldwide and other relevant documents were also used as secondary sources.
MODELS AND OPERATIONALIZATION OF VARIABLES
Econometric models
The econometric models that were used in this research are based on the scientific requirements of the variables (dependent and explanatory) that are considered and models used by other researchers with similar topics. It is worth considering the methods and models used by other researchers for comparing results of the researches.
Econometric model of farm income
The factors affecting agricultural production are expected to affect the total agricultural income of farm operators. For the sake of details, additional functional form for crop income is also specified.
In analysing the total farm income (farminco) and crop income (cropinco) the Ordinary Least Squares (OLS) is used. The livestock income (estimated value of livestock) is included in the total farm income model. The justification for using OLS model is that total farm and crop income are continuous dependent variables and they are expected to take a non-zero value for all farm households (Endale, 2011, p. 35).
y = X’ β + ε
Where:
y= is the dependent variable;
X= vector of explanatory variables;
β= the parameter to be estimated;
ε= the error term.
Then, the functional notation of the dependent and independent variables is:
farminco= β0 + β1lansize + β2age + β3age2+ β4gender + β5eduhead + β6famsize + β7oxen + β8ferti + β9seed + β10irri + β11cred + β12extagent+ β13landfert+ β14rain+ β15disaverage + β16zerograz +ε cropinco= β0 + β1lansize + β2age + β3age2 +β4gender + β5eduhead + β6famsize + β7oxen + β8ferti + β9seed + β10irri + β11cred + β12extagent+ β13landfert+ β14rain+ β15disaverage+ β16zerograz + ε
The descriptions of dependent and independent variables that are used in the above functional notation are stated below.
Dependent variables
Household crop income (prodbirr)
Crop income is the total value of crops produced in the production year of 2011/12 (2004 E.C.4).
Household farm income (farminco)
Farm income is the total value of crops and livestock in the year 2011/12 (2004 E.C.)
Independent variables
Land holding size (totalland)
This variable is measured in terms of hectares. It is also hypothesized that the larger the land holding size (own and rented cultivated land) of the farm household, the higher the volume of production and farm income.
Age of the household head (age)
with the learning process of households in handling their overall agricultural practices. It is expected to influence farm income positively as long as farmers are in the active age range.
Gender (gender)
In Ethiopia, the contribution of both women and men to the productivity of agriculture is vital. But the opportunities are relatively skewed towards men compared to female household heads. According to Endale (2011, p. 24) gender bias towards access to land and education for men is the cause of poor performance of women in agriculture. Hence, it is hypothesized that male household heads are expected to produce more and get better agricultural income compared to female household heads. Gender is a dummy variable 1 if the household head is male and 0 otherwise.
Educational status of the head (educlevel)
Educated households are expected to have better exposure to information that enhances agricultural production. They are also expected to be innovators in accepting new waysof doing things. This variable is measured in terms of the number of years of schooling thatis expected to have a positive impact on agricultural production and hence income.
Family size (adultequiva)
Family members of the household (adult equivalent)5 are a potential source of labour in the agricultural sector. Households with many family members will have the chance to diversify their agricultural activities and rent the land of others. Hence, it is hypothesised that the larger the number of members of the family who are engaged in agricultural activities, the greater the income from agriculture will be.
Oxen (oxenown)
These are the key assets in the rural areas of the country. A household needs two oxen to plough a plot. For smooth management and timeous cultivation of land, a household needs a pair of oxen. Agricultural production is directly influenced by the ownership of oxen. It is, therefore, hypothesised that the larger the number of oxen the household has, the more the income from agriculture will be.
Technologies
According to Negatu (2006, p. 153), in Ethiopian agriculture, biological and chemical technologies are the most promoted technologies. The widely used technologies by farm operators in Ethiopia are fertilizer(fertitotal), improved seeds(imprseed) and irrigation(irriown) technologies. The variables fertilizer (fertitotal) and irrigation (irriown) are continuous variables measured in terms of kg/Tsimad and in hectares respectively. The remaining variable (imprseed)will take a dummy variable that is 1for households using improved seed and 0 otherwise. Moreover, it is hypothesized that agricultural production is positively influenced by the application of each of these technologies. These variables are also proxy variables for the availability of fodder which enhances the income of farm operators from their livestock income.
Access to credit (amountborro)
Capital is the scarcest asset in the developing countries in general and rural areas in particular. There is a need for money to adopt new technologies such as yield increasing inputs. In line with this, Ellis (1992, p. 128) stated that input delivery should be combined with credit provision in order to reduce the working capital constraints to adopting new inputs forfarm households. In Tigray region, Dedebit Credit and Saving Institution (DECSI) provides the microfinance accessible to farmers in the rural areas. Farmers may also get “in-kind” loans such as fertilizers and improved seeds from the farmers’ cooperatives in their communities. Thus, this variable is measured in terms of the Ethiopian currency (Birr) that the household took in the production year. It is hypothesized that the availability of rural credit is expected to increase agricultural production and income.
DECLARATION
DEDICATION
ACKNOWLEDGMENTS
ABSTRACT
ABBREVIATIONS
DEFINITION OF LOCAL TERMS
LIST OF TABLES
LIST OF FIGURES
CHAPTER 1: INTRODUCTION
1.1 BACKGROUND OF THE STUDY
1.2 PROBLEM STATEMENT
1.3 OBJECTIVES OF THE STUDY
1.4 RESEARCH QUESTIONS
1.5 SCOPE AND LIMITATIONS OF THE STUDY
1.6 IMPORTANCE OF THE STUDY
1.7 STRUCTURE OF THE THESIS
CHAPTER 2: LITERATURE REVIEW
2.1 INTRODUCTION
2.2 DEFINITION OF KEY CONCEPTS
2.3 GENERAL ISSUES OF AGRICULTURAL PRODUCTION
2.4 FACTORS AFFECTING AGRICULTURAL PRODUCTION AND FARM INCOME
2.5. FACTORS AFFECTING AGRICULTURAL MARKETING
2.6 DETERMINANT FACTORS FOR OFF-FARM ACTIVITIES AND OFF-FARM INCOME
2.7 CONCLUSIONS
CHAPTER 3: AGRARIAN POLICIES AND AGRICULTURAL PRODUCTION IN ETHIOPIA
3.1 INTRODUCTION AND BACKGROUND OF THE STUDY AREA
3.2 AGRARIAN POLICIES AND AGRICULTURAL PRODUCTION DURING THE IMPERIAL REGIME (PRE-1974)
3.3 AGRARIAN POLICIES AND AGRICULTURAL PRODUCTION DURING THE DERG REGIME (1974-1991)
3.4 AGRARIAN POLICIES AND AGRICULTURAL PRODUCTION DURING THE ETHIOPIAN PEOPLE’S REVOLUTIONARY AND DEMOCRATIC FRONT (EPRDF) REGIME (SINCE 1991)
3.5 BRIEF BACKGROUND OF THE STUDY AREA
3.6 CONCLUSION
CHAPTER 4: RESEARCH DESIGN AND METHODOLOGY
4.1 INTRODUCTION
4.2 RESEARCH DESIGN
4.3 DATA TYPE
4.4 DATA SOURCES
4.5. MODELS AND OPERATIONALIZATION OF VARIABLES
4.6 SAMPLING DESIGN AND SAMPLING METHODS
4.7 DATA PROCESSING AND ANALYSIS
4.8 ISSUES OF VALIDITY AND RELIABILITY
4.9 CONCLUSION
CHAPTER 5: RESULTS AND DISCUSSION
5.1 INTRODUCTION.
5.2 SOCIO-ECONOMIC CHARACTERISTICS OF RESPONDENTS
5.3 THE FACTORS AFFECTING AGRICULTURAL PRODUCTION AND THEIR IMPACT ON THE INCOME OF THE FARM HOUSEHOLDS
5.4 THE MAJOR CHALLENGES OF THE HOUSEHOLD HEADS IN MARKETING THEIR PRODUCE
5.5 THE MAJOR DETERMINANT FACTORS OF FARM OPERATORS TO PARTICIPATE IN OFF-FARM ACTIVITIES AND THEIR IMPACTS ON THE OFF-FARM INCOME.
5.6 A CRITICAL ASSESSMENT OF AGRICULTURAL PRODUCTION IN THE REGIONAL STATE OF TIGRAY
5.7 CONCLUSION
CHAPTER 6: SUMMARY, CONCLUSION AND RECOMMENDATIONS
6.1 INTRODUCTION
6.2 SUMMARY
6.3 CONCLUSIONS
6.4 RECOMMENDATIONS
6.5 AREAS FOR FURTHER RESEARCH
REFERENCES
GET THE COMPLETE PROJECT
FACTORS AFFECTING AGRICULTURAL PRODUCTION IN TIGRAY REGION, NORTHERN ETHIOPIA
