Kedir Greener Journal of Agricultural Sciences Vol. 9(2), pp. 119-137, 2019 ISSN: 2276-7770 Copyright ©2019, the copyright of this article is retained by the author(s) DOI Link: http://doi.org/10.15580/GJAS.2019.2.010919010 https://gjournals.org/GJAS Impact of Improved Soybean (Belessa-95) Variety on Income among Smallholder Farmers in Bambasi Woreda, Benishangul Gumuz Regional State Musba Kedir Ethiopian Institute of Agricultural Research (EIAR), Planning, Monitoring and Evaluation Researcher ARTICLE INFO ABSTRACT Article No.: 010919010 Type: Research DOI: 10.15580/GJAS.2019.2.010919010 The importance of agricultural technology in enhancing the welfares of farmers can be realized when yield gain from the technologies results in meaningful income gain. This article aimed to assess economic impact of improved soybean (Bellessa-95) variety on income among farm households in Bambasi District, BGRS. In this study a multi-stage stratified sampling technique was employed to select rural kebeles and households. Three rural kebeles were selected randomly. Structured interview schedule was developed, pre-tested and used for collecting the essential quantitative data for the study from 134 randomly selected households. Descriptive statistics and propensity score machining (PSM) models were employed to analyze data. Results of descriptive analysis showed that there were statistically significant differences between adopter and non-adopter households with distance to market, livestock ownership, and frequency of extension visit, farm income as well as number of oxen owned. Consistent with the findings of previous studies, regression results showed that adoption of improved soybean has a positive and significant effect on farm income by which adopters are better-off than non-adopters. Based on results obtained it is recommended to continuous training in improved soybean production. Promoting farmers to form or join cooperatives. Strengthening demonstration centers and Farmers Training Centers (FTC). Transaction costs should be reduced and scaling up and diffusion of improved soybean varieties in the study area should be broadened. Submitted: 09/01/2019 Accepted: 12/01/2019 Published: 09/04/2019 *Corresponding Author Mr. Musba Kedir E-mail: Kedirmusba44@ gmail.com Phone: +251913917911 Keywords: Adoption; Bambasi; Impact; Soybean; and PSM Return to Content View [Full Article – PDF] [Full Article – HTML] [Full Article – EPUB] Post-Publication Peer-review Rundown View/get involved, click [Peer-review] REFERENCES Abadie A. and Imbens A. 2006. Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica , issue 1, pages 235-267. ADB (Asian Development Bank). 2006. Impact evaluation: methodological and operational issues. Economic and Research Department. Alene A.D., Poonyth D. and Hassan R.M. 2000. Determinants of Adoption and Intensity of Use of Improved Maize Varieties in the Central Highlands of Ethiopia: A Tobit Analysis. Agrekon, Vol 39(4) Asfaw Tilahun. 2013. Impact of Microfinance on the Livelihood of Smallholder Farmers: The Case of Oromia Credit and Saving Share Company, Grawa Branch, East Haraghe Zone, Oromia National. Regional State, Ethiopia. Msc Thesis Haramaya University School of Graduate Studies. Becker, J.L. 2000. Evaluating the Impact of Development Projects on Poverty: A handbook for Practitioners. The World Bank Washington, D.C. Berhanu Kassa, Bihon Kassa and Kibrom Aregawi. 2014. Adoption and Impact of Agricultural Technologies on Farm Income: evidence from Southern Tigray, Northern Ethiopia. International Journal of Food and Agricultural Economics ISSN 2147-8988 Vol. 2: 91-106. Bingxin Y. Alejandro N., Funes S. Asrat Gemessa. 2011. Cereal Production and Technology Adoption in Ethiopia. IFPRI Discussion Paper 0113. Development Strategy and Governance Division. Bryson, A, Dorsett R and Purdon S. 2002. The use of Propensity Score Matching in the Evaluation of Labor Market Policies. Working Paper No. 4. Department for Work and Pensions. Caliendo M. and Koping S. 2008. Some Practical Guidance for the Implementation of Propensity Score Matching, Discussion Paper No.1588, University of Cologne. CSA (Central Statistical Agency of Ethiopia). 2015. Population Stabilization Report Ethiopia. Addis Ababa, Ethiopia. Davis, K., Ephraim Nykon, Edward K, Daniel Ayalew, Martins O, Richard M and Jackson N. 2010. Impact of Farmer Field Schools on Agricultural Productivity and Poverty in East Africa. IFPRI Discussion Paper 992. Dehejia, R.H. and Wahba S. 2002. Propensity Score-Matching Methods for Non- experimental Causal Studies. The Review of Economics and Statistics, Vol. 84(1): 151-161. Dehejia and Wahbha, 2002; Smith and Todd, 2005) FAO. 2012. Crop and Food Security Assessment Mission Geremew Kefyalew. 2012. Analysis of Smallholder Farmer’s Participation in Production and Marketing of Export Potential Crops: The Case of Sesame in Diga District, East Wollega Zone of Oromia Regional State. MA Thesis, Addis Ababa University Hossain, S., Alamgir, M. & Croach, R. 1992. Patterns and determinants of adoption of farm practices: Some evidence from Bangladesh. Agric. Systems, 38:1-15. Jalan J.and Ravallion M. 2003. Estimating the Benefit Incidence of an Antipoverty Program by Propensity Score Matching. Journal of Business and Economics Statistics, Vol. 21 (1):PP. 19-30. Kathelen O. 2010. Measuring the Impact of Microfinance. Grameen Foundation Publication Series. PP 7. Liebenehm S. Affognon H. Waibel H. 2009. Impact Assessment of Livestock Research and Development in West Africa: A Propensity Score Matching Approach Mariapia Mendola. 2007. Agricultural technology adoption and poverty reduction: A propensity-score matching analysis for rural Bangladesh. University of Milano-Bicocca and Centro Studi L. d’Agliano, Milano, Italy. Mekuria Aweke, 2013. Factors Influencing Adoption of Improved Maize Varieties: The Case of Goro- Gutu Woreda of Eastern Hararghe, Ethiopia, MSc. Thesis presented to school of graduate studies of Haramaya University. Mengistu Ketema .2003. Impact of Technology on Wheat Production in Bale Highland: The case of Smallholder farmers of Oromia Regional State, Ethiopia.” Msc thesis in Agricultural Economics. Presented to Graduate Studies of Haramaya University. Minyahel Fekadu, 2007. Analysis of Factors Influencing Intensity of Adoption of Improved Bread wheat Production Package in Jama District. MSc. Thesis, Haramaya University Rosenbaum, P. and Rubin, D. 1983. The Central role of the Propensity Score in observational Studies for Causal effects. Biometrica, 70(1): 41-55. Solomon Tiruneh. 2012. Impact of Improved Barley Scale Up/Out Program on Household Food Security in Meket District, North Eastern Ethiopia M.Sc. thesis Haramaya University. Tadesse, Million, and Kassa Belay. 2004. Factors influencing adoption of soil conservation measures in Southern Ethiopia: the case of Gununo area.” Journal of Agriculture and Rural Development in the Tropics and Subtropics (JARTS) 105. 49-62. Tesfaye Zegeye and Alemu Haileye. 2001. Adoption of Improved maize technologies and Inorganic Fertilizer in North Western Ethiopia. Addis Ababa, Ethiopian Institute of Agricultural Research. UNDP (United Nations Development Program). 2014. Ethiopia: Quarterly Economic Brief. Third Quarter, Addis Ababa, Ethiopia. Yenealem Kassa, Ranjan S. Belaineh Legesse. 2013. Determinants of adoption of improved maize varieties for male headed and female headed households in West Harerghe zone, Ethiopia. Cite this Article: Kedir M (2019). Impact of Improved Soybean (Belessa-95) Variety on Income among Smallholder Farmers in Bambasi Woreda, Benishangul Gumuz Regional State. Greener Journal of Agricultural Sciences 9(2): 119-137, http://doi.org/10.15580/GJAS.2019.2.010919010.
