dc.contributor.author |
SILESHI ADELLA MULUNEH |
|
dc.contributor.author |
Solomon Tekalign (Ph.D) |
|
dc.contributor.author |
Solomon Asefaw (Ph.D) |
|
dc.date.accessioned |
2023-05-10T06:27:57Z |
|
dc.date.available |
2023-05-10T06:27:57Z |
|
dc.date.issued |
2022-06 |
|
dc.identifier.uri |
http://ir.haramaya.edu.et//hru/handle/123456789/5764 |
|
dc.description |
128 |
en_US |
dc.description.abstract |
The study was conducted in rural kebeles of Dire Dawa focusing on the impact of Climate
Smart Agricultural practices on household food security together with the identification of
Climate Smart Agricultural Practices being implemented and the factors affecting the
practices in the study area. A two-stage sampling technique was employed to select sample
from 5 kebeles to get a total of 377 households. A cross-sectional research design was used to
collect and analyze data from the households. Both qualitative and quantitative methods were
employed. Primary and secondary data were also used. The Qualitative data was analyzed
through interpretation and conceptual generalization; and for the quantitative data both
descriptive statistics binary logit model and Propensity Score Matching model were employed
to analyze the relationship between the dependent and explanatory variables. Descriptive
statistics was employed to describe background characteristics of sampled units; to analyze
data related to attitude of the farmers towards the occurrence of climate variability and
change. It was also used to describe the types of Climate Smart Agricultural practices
implemented. The household food security was measured by using the different indicators like
Caloric Intake, Household Food Consumption Score and Household Dietary Diversity Score.
For the impact assessment, Binary Logit model and Propensity Score Matching approach
were used to identify main factors affecting farmers‟ Climate Smart Agricultural practices and
the impacts of the Climate Smart Agriculture practices on household food security,
respectively. Statistical tests like t-test and chi-squared were also used to test differences in
characteristics between practicing and non-practicing households of Climate Smart
Agricultural practices. The Propensity Matching Model output confirmed that practicing
Climate Smart Agriculture increased household income from crop and livestock production by
more than 30% and 32%, respectively. Based on the empirical findings of this study, it is
recommended that experienced household heads to share their experiences on the local CSA
practices; it is also recommended that government to provide crop and livestock that are High
Yielding Varieties and best suited to the climatic conditions; development agents to closely
follow up the farming households and provide technical guidance on CSA practices at the
farm level; food security programs need to consider the development of irrigation
infrastructure to increase the households „access to irrigation water; and it needs to design a
revolving fund in the interventions that help to provide agricultural inputs; and finance other
income generating businesses of the farming households to diversify livelihood. |
en_US |
dc.description.sponsorship |
Haramaya University, Haramaya |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Haramaya University, Haramaya |
en_US |
dc.subject |
Climate Smart Agriculture, Food Security, Dire Dawa, Propensity Score Matching Binary Logit Model. |
en_US |
dc.title |
PRACTICES OF CLIMATE SMART AGRICULTURE AND IMPACTS ON THE HOUSEHOLD FOOD SECURITY IN RURAL KEBELES OF DIRE DAWA ADMINISTRATION, ETHIOPIA |
en_US |
dc.type |
Thesis |
en_US |