The study evaluated impact of non-farm activities on wellbeing of rural household using cross-sectional data. Household’s consumption expenditure per adult equivalent was analyzed to measure household wellbeing. Multi-stage sampling technique was employed to select sample households from three Kebeles. Both primary and secondary data were used. Data were collected primarily through Semi-structured survey questionnaire from 178 households. Descriptive statistics and propensity score matching model were used to analyze the data. Propensity score matching (PSM) technique of impact evaluation preferred to overcome counterfactual problem and selection bias. Analysis results show that non-farm activities have increased consumption expenditure per adult equivalent ranging from 29.1% to 36.7% for participant households. In conclusion, participant households were more likely to be wellbeing as compared to the non-participant households. The result from the logistic estimator also revealed that participation in non-farm activities was significantly associated with variables such as age, education, adult equivalent size, cultivable land size, farm experience, and distance from main road, tropical livestock unit and access to nonfarm training. Therefore, such rural development planners and other stakeholders should consider the roles of these variables within the selection of participants for desired impact on economic wellbeing.
| Published in | Humanities and Social Sciences (Volume 8, Issue 6) |
| DOI | 10.11648/j.hss.20200806.13 |
| Page(s) | 182-190 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2020. Published by Science Publishing Group |
Non-farm Activities, Impact, Propensity Score Matching, Wellbeing
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APA Style
Fami Abdurezak, Adinan Ahmed. (2020). Impact of Non-farm Activities on Wellbeing of Rural Household, the Case of Kersa District, Eastern Hararghe Zone, Ethiopia. Humanities and Social Sciences, 8(6), 182-190. https://doi.org/10.11648/j.hss.20200806.13
ACS Style
Fami Abdurezak; Adinan Ahmed. Impact of Non-farm Activities on Wellbeing of Rural Household, the Case of Kersa District, Eastern Hararghe Zone, Ethiopia. Humanit. Soc. Sci. 2020, 8(6), 182-190. doi: 10.11648/j.hss.20200806.13
AMA Style
Fami Abdurezak, Adinan Ahmed. Impact of Non-farm Activities on Wellbeing of Rural Household, the Case of Kersa District, Eastern Hararghe Zone, Ethiopia. Humanit Soc Sci. 2020;8(6):182-190. doi: 10.11648/j.hss.20200806.13
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Download@article{10.11648/j.hss.20200806.13,
author = {Fami Abdurezak and Adinan Ahmed},
title = {Impact of Non-farm Activities on Wellbeing of Rural Household, the Case of Kersa District, Eastern Hararghe Zone, Ethiopia},
journal = {Humanities and Social Sciences},
volume = {8},
number = {6},
pages = {182-190},
doi = {10.11648/j.hss.20200806.13},
url = {https://doi.org/10.11648/j.hss.20200806.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.hss.20200806.13},
abstract = {The study evaluated impact of non-farm activities on wellbeing of rural household using cross-sectional data. Household’s consumption expenditure per adult equivalent was analyzed to measure household wellbeing. Multi-stage sampling technique was employed to select sample households from three Kebeles. Both primary and secondary data were used. Data were collected primarily through Semi-structured survey questionnaire from 178 households. Descriptive statistics and propensity score matching model were used to analyze the data. Propensity score matching (PSM) technique of impact evaluation preferred to overcome counterfactual problem and selection bias. Analysis results show that non-farm activities have increased consumption expenditure per adult equivalent ranging from 29.1% to 36.7% for participant households. In conclusion, participant households were more likely to be wellbeing as compared to the non-participant households. The result from the logistic estimator also revealed that participation in non-farm activities was significantly associated with variables such as age, education, adult equivalent size, cultivable land size, farm experience, and distance from main road, tropical livestock unit and access to nonfarm training. Therefore, such rural development planners and other stakeholders should consider the roles of these variables within the selection of participants for desired impact on economic wellbeing.},
year = {2020}
}
TY - JOUR T1 - Impact of Non-farm Activities on Wellbeing of Rural Household, the Case of Kersa District, Eastern Hararghe Zone, Ethiopia AU - Fami Abdurezak AU - Adinan Ahmed Y1 - 2020/11/19 PY - 2020 N1 - https://doi.org/10.11648/j.hss.20200806.13 DO - 10.11648/j.hss.20200806.13 T2 - Humanities and Social Sciences JF - Humanities and Social Sciences JO - Humanities and Social Sciences SP - 182 EP - 190 PB - Science Publishing Group SN - 2330-8184 UR - https://doi.org/10.11648/j.hss.20200806.13 AB - The study evaluated impact of non-farm activities on wellbeing of rural household using cross-sectional data. Household’s consumption expenditure per adult equivalent was analyzed to measure household wellbeing. Multi-stage sampling technique was employed to select sample households from three Kebeles. Both primary and secondary data were used. Data were collected primarily through Semi-structured survey questionnaire from 178 households. Descriptive statistics and propensity score matching model were used to analyze the data. Propensity score matching (PSM) technique of impact evaluation preferred to overcome counterfactual problem and selection bias. Analysis results show that non-farm activities have increased consumption expenditure per adult equivalent ranging from 29.1% to 36.7% for participant households. In conclusion, participant households were more likely to be wellbeing as compared to the non-participant households. The result from the logistic estimator also revealed that participation in non-farm activities was significantly associated with variables such as age, education, adult equivalent size, cultivable land size, farm experience, and distance from main road, tropical livestock unit and access to nonfarm training. Therefore, such rural development planners and other stakeholders should consider the roles of these variables within the selection of participants for desired impact on economic wellbeing. VL - 8 IS - 6 ER -
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