This study analyzed factors affecting modern agricultural technology adoption by farmers and the impact of technology adoption decision on the welfare of households in the study area. The data used for the study were obtained from 145 randomly selected sample households in the study area. Binary logit model was employed to analyze the determinants of farmers’ decisions to adopt modern technologies. Moreover, the average effect of adoption on household incomes and expenditure were estimated by using propensity score matching method. The result of the logistic regression showed that household heads’ education level, farm size, credit accessibility, perception of farmers about cost of the inputs and off-farm income positively and significantly affected the farm households’ adoption decision; while family size affected their decision negatively and significantly. The result of the propensity score matching estimation showed that the average income and consumption expenditure of adopters are greater than that of non-adopters. Based on these findings it is recommended that the zonal and the woreda leaders extension agents farm and education experts, policy makers and other development oriented organizations have to plan in such a way that the farm households in the study area will obtain sufficient education, credit accessibilities and also have to train farmers to make them understand the benefits obtained from adopting the new technologies. These bodies have also to arrange policy issues that improve farm labour participation of household members and also to arrange the ways in which farmers obtain means of income outside farming activities.
Table of Contents
1. INTRODUCTION
1.1 Background of the study
1.2 Statement of the problem
1.3 The research questions
1.4 Objective of the study
1.5 Significance of the study
1.6 Scope and limitation of the Study
1.7. Organization of the paper
2. LITERATURE REVIEW
2.1. Definition of agricultural technology adoption
2.2. Theoretical Background of Agricultural technology adoption and its impacts.
2.2.1 Why agricultural technologies adoption is required?
2.2.2 Effects of Adoption of Modern Agricultural Technologies
2.2.3 Estimating the impact of the technology adoption by incomes of farm households
2.2.4 Adoption of Modern Agricultural Technology in Ethiopia
2.3 Empirical Studies on Determinants and impacts of Agricultural technology adoption
3. METHODOLOGY
3.1 Description of the study area
3.1.1 Location and area
3.1.2 Climate and soils
3.1.3 Vegetation and wild life
3.1.4 Main crops grown
3.1.5 Education
3.1.6 Financial institutions
3.1.7 Population
3.2 Sampling procedure and sample size determination
3.2.1 Sampling procedure
3.2.2 Sample size determination
3.3 Method of Data Collection
3. 4. Econometric Model Specification and Estimation Procedure
3.4.1. Estimating the determinants of technology adoption
3.4.2 The impacts of modern agricultural technology adoption on welfare of households
4. RESULTS AND DISCUSSION
4.1 Descriptive Analysis
4.2 Results of Econometric Analysis
4.3. Estimating the impact of agricultural technology adoption decision
4.4 Sensitivity test for estimated average treatment effects (ATT)
5. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
5.1 Summary
5.2 Conclusions
5.3. Recommendations
6. REFERENCES
Objectives and Research Themes
This thesis examines the factors influencing the adoption of modern agricultural technologies among smallholder farmers in the Gulliso District of Ethiopia and assesses the welfare impact of these adoption decisions on household income and consumption expenditure.
- Determinants of modern agricultural technology adoption among farm households.
- Assessment of the causal impact of adoption on household welfare using propensity score matching.
- Analysis of socio-economic and institutional factors, including credit access and off-farm income.
- Evaluation of the relationship between input costs, farm size, and technology usage.
- Formulation of policy recommendations for regional agricultural development and poverty reduction.
Excerpt from the Book
1.1 Background of the study
There has been much discussion on the need to increase productivity and sustainability in agriculture globally in the medium to long terms, but much less information is available on specific means to achieve this aim. Increasing agricultural productivity is critical to meet expected rising demand and, as such, it is instructive to examine recent performance in cases of modern agricultural technologies (FAO, 2012).
It is no longer possible to meet the needs of increasing numbers of world population and to achieve food security objectives by expanding areas under cultivation since the fertile land is not increasing over time. But this problem can only be solved more by increasing agricultural productivity of farm households. However, achieving agricultural productivity growth will not be possible without developing and disseminating yield-increasing technologies and application of these technologies by farm households. Agricultural research and technological improvements are therefore crucial to increase agricultural productivity and thereby reduce poverty and meet demands for food without irreversible degradation of the natural resource base. Agricultural research and technological improvements are also crucial in reducing poverty (Solomon (2010); Solomon et al, 2011).
Barriers to technology adoption, initial asset endowments, and constraints to market access may all inhibit the ability of the poorest to participate in the gains from agricultural productivity growth. This agricultural productivity growth can also be driven by improved farm technologies, including improved seeds, fertilizer, and water control (Johnston & Kilby, 1975).
Summary of Chapters
1. INTRODUCTION: This chapter introduces the study, its objectives, research questions, and the significance of analyzing technology adoption to improve agricultural productivity and food security in Ethiopia.
2. LITERATURE REVIEW: This section provides a theoretical overview of technology adoption and reviews empirical studies regarding the socio-economic, institutional, and environmental factors influencing farmer behavior.
3. METHODOLOGY: This chapter details the study area, the sampling procedures used to select the 145 households, data collection methods, and the specific econometric models (Logit and Propensity Score Matching) employed for analysis.
4. RESULTS AND DISCUSSION: This chapter presents the descriptive statistics and the empirical findings regarding the determinants of technology adoption and the estimated average treatment effects on household welfare.
5. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS: This final chapter synthesizes the findings and proposes specific policy interventions for zonal and district leaders to enhance agricultural technology adoption and rural livelihoods.
Keywords
Agriculture, Farm household, Technology Adoption, Logit Model, impact, propensity score match, Productivity, Food security, Ethiopia, West Wollega, Gulliso District, Smallholder farmers, Econometrics, Rural development, Welfare.
Frequently Asked Questions
What is the primary focus of this research?
The research focuses on identifying the socio-economic and institutional factors that determine whether farmers in Gulliso District adopt modern agricultural technologies, such as improved seeds and fertilizers.
What is the core research objective?
The core objective is to analyze the determinants of technology adoption and to measure the impact of these adoption decisions on the welfare—specifically income and consumption—of farm households.
Which scientific methods are utilized?
The study employs a Binary Logit Regression Model to identify determinants of adoption and Propensity Score Matching (PSM) to estimate the Average Treatment Effect on the Treated (ATT) regarding household income and expenditure.
What are the key themes addressed?
The work covers themes such as agricultural productivity growth, the role of credit access, the influence of education on adoption, the impact of off-farm income, and the mitigation of production risks.
What does the final analysis reveal about technology adoption?
The analysis reveals that education, credit accessibility, favorable perceptions of input costs, farm size, and participation in off-farm labor are positive, significant drivers of technology adoption.
How is the sample for this study determined?
The study uses random sampling to select 145 households from six administrative Kebeles within the Gulliso District, ensuring a balance between adopters and non-adopters.
What is the significance of propensity score matching here?
It is used to compare the welfare outcomes of adopters against a statistically comparable group of non-adopters, effectively reducing bias in estimating the causal impact of the technology.
How do farm size and family size impact adoption?
Farm size is found to have a positive and significant impact, whereas family size shows a negative impact, possibly due to the diversion of household income toward immediate consumption rather than agricultural investment.
- Citar trabajo
- Merga Challa (Autor), 2013, Determining Factors and Impacts of Modern Agricultural Technology Adoption in West Wollega, Múnich, GRIN Verlag, https://www.grin.com/document/280336
