Impact of adopting improved Arabica varieties on the livelihood of organic coffee producers’ of Ethiopia: Continuous treatment approach

References

• Abdu, A., & Gedeo, T. A. (2013). Highland home garden agroforestry system- case study, in farmers’ strategies for adapting to and mitigating climate variability and change through agroforestry in Ethiopia and Kenya., pp. 1–15, Oregon state university, Corvallis, OR, USA.,
   Google Scholar
• Agriculture and Natural Resource Bureau Bureau. (2021). Annual report.
   Google Scholar
• Amare, M., Asfaw, S., & Shiferaw, B. (2012). Welfare impacts of maize-pigeon pea intensification in Tanzania. Agricultural Economics, 43(1), 1–14.
   Web of Science ®Google Scholar
• Amsalu, A. (2015). Institutional context for soil resources management in Ethiopia: A review: September 2015., Addis Ababa.
   Google Scholar
• Ayele, A., Worku, M., & Bekele, Y. (2021). Trend, instability and decomposition analysis of coffee production in Ethiopia (1993–2019). Heliyon, 7(9), e08022. https://doi.org/10.1016/j.heliyon.2021.e08022
   PubMed Web of Science ®Google Scholar
• Bia, M., & Mattei, A. (2008). A Stata package for the estimation of the dose–response function through adjustment for the generalized propensity score. The Stata Journal: Promoting Communications on Statistics and Stata, 8(3), 354–373. https://doi.org/10.1177/1536867X0800800303
   Google Scholar
• Biru, W. D., Zeller, M., & Loos, T. K. (2020). The impact of agricultural technologies on poverty and vulnerability of smallholders in Ethiopia: a panel data analysis. Social Indicators Research, 147(2), 517–544. 5-019-02166-0. https://doi.org/10.1007/s11205-019-02166-0
   Web of Science ®Google Scholar
• CSA (Central Statistical Agency). (2015). Federal democratic republic of Ethiopia. Agricultural sample survey 2014/2015 (2007 E.C.). CSA, Addis Ababa.
   Google Scholar
• CSA (Central Statistical Agency). (2018). Reports on area and production of crops (Private Peasant Holdings, Meher Season). Addis Ababa.
   Google Scholar
• DANRB (District Agriculture and Natural Resource Bureau). (2021). District Agriculture and Natural Resources Bureau, District 4th quarter agricultural and natural resource report, 2020/21. Kochore District.
   Google Scholar
• Djebbari, H., & Smith, J. (2008). Heterogeneous impacts in PROGRESA. Journal of Econometrics, 145(1-2), 64–80. https://doi.org/10.1016/j.jeconom.2008.05.012
   Web of Science ®Google Scholar
• GAIN (Global Agricultural Information Network). (2019). Ethiopia coffee annual report. Assessments of commodity and trade issues official U.S. government Required Report - public distribution Report Number: ET1904,
   Google Scholar
• Gao, Y., Niu, Z. H., Yang, H., & Yu, L. (2019). Impact of green control techniques on family farms’ welfare. Ecological Economics, 161, 91–99. https://doi.org/10.1016/j.ecolecon.2019.03.015
   Web of Science ®Google Scholar
• Gelaw, F., Speelman, S., Van, H., & Van, G. (2016). Farmers’ marketing preferences in local coffee markets: Evidence from a choice experiment in Ethiopia. Food Policy. 61, 92–102. https://doi.org/10.1016/j.foodpol.2016.02.006
   Web of Science ®Google Scholar
• Guardabascio, B., & Ventura, M. (2014). Estimating the dose-response function through the GLM approach. http://mpra.ub.uni-muenchen.de/45013/. Accessed 15 June 2017.
   Google Scholar
• Hirano, K., & Imbens, G. W. (2004). The propensity score with continuous treatments. In A. Gelman and X. Meng (Eds.), Applied Bayesian modeling and causal inference from incomplete-data perspectives.
   Google Scholar
• Hou, X. K., Liu, T. J., & Huang, T. (2020). Adoption behavior and income effects of green agricultural technology for farmers. Journal of Northwest University of Agriculture and Forestry, (Social Science Edition). 3, 121–130. https://doi.org/10.1371/journal.pone.0267101
   Google Scholar
• Houeninvo, G. H., Quenum, C. V. C., & Nonvide, G. M. A. (2019). Impact of improved maize variety adoption on smallholder farmers’ welfare in Benin. Economics of Innovation and New Technology, 29(8), 831–846. https://doi.org/10.1080/10438599.2019.1669331.
   Web of Science ®Google Scholar
• Huang, T. T., Huang, Q. H., & Hu, J. F. (2020). Research on the impact of pilot determination on the economic benefits of family farms. World Agriculture, 9, 56–64.
   Google Scholar
• Irene, B., Aloyce, H., Elizaphan, J. O. R., & Kenneth, M. (2018). Do dairy market hubs improve smallholder farmers’ income? The Case of Dairy Farmers in the Tanga and Morogoro Regions of Tanzania, Tanzania Journal of Agricultural Sciences, 18(1), 1–12. https://doi.org/10.1080/03031853.2018.1481758.
   Google Scholar
• Kassie, M., Jaleta, M., & Mattei, A. (2014). Evaluating the impact of improved maize varieties on food security in Rural Tanzania: Evidence from a continuous treatment approach. Food Security, 6(2), 217–230. https://doi.org/10.1007/s12571-014-0332-x
   Web of Science ®Google Scholar
• Kassie, M., Shiferaw, B., & Muricho, G. (2011). Agricultural technology, crop income, and poverty alleviation in Uganda. World Development, 39(10), 1784–1795. https://doi.org/10.1016/j.worlddev.2011.04.023
   Web of Science ®Google Scholar
• Kippie, T. (2002). Five thousand years of sustainability? A case study on Gedeo land use. (Southern Ethiopia). Treemail Publishers.
   Google Scholar
• Kluve, J., Schneider, H., Uhlendorff, A., & Zhao, Z. (2007). Evaluating continuous training programs using the generalized propensity score. Discussion Paper No. 3255.
   Google Scholar
• Kluve, J., Schneider, H., Uhlendorff, A., & Zhao, Z. (2012). Evaluating continuous training programmes by using the generalized propensity score. Journal of the Royal Statistical Society Series A: Statistics in Society, 175(2), 587–617. https://doi.org/10.1111/j.1467-985X.2011.01000.x
   Web of Science ®Google Scholar
• Kodama, Y. (2007). New role of cooperatives in Ethiopia: The case of Ethiopian coffee farmers cooperatives. African Study Monographs, Suppl35, 87–108.
   Google Scholar
• Li, J., & Fraser, M. W. (2015). Evaluating dosage effects in a social-emotional skills training program for children: An application of generalized propensity scores. Journal of Social Service Research, 41(3), 345–364. https://doi.org/10.1080/01488376.2014.994797
   Web of Science ®Google Scholar
• Liu, J., & Florax, R. (2014. In 2014 Annual Meeting, July 27–29, 2014, Minneapolis, Minnesota, USA (No. 169804), USA. The effectiveness of international aid: A generalized propensity score analysis Agricultural and Applied Economics Association.
   Google Scholar
• Ma, W., & Abdulai, A. (2019). IPM adoption, cooperative membership and farm economic performance: Insight from apple farmers in China. China Agricultural Economic Review, 11(2), 218–236. https://doi.org/10.1108/CAER-12-2017-0251
   Web of Science ®Google Scholar
• Magrini, E., & Vigani, M. (2016). Technology adoption and the multiple dimensions of food security: the case of maize in Tanzania. Food Security, 8(4), 707–726. https://doi.org/10.1007/s12571-016-0593-7
   Web of Science ®Google Scholar
• Makate, C., Wang, R., Makate, M., & Mango, N. (2017). Impact of drought tolerant maize adoption on maize productivity, sales and consumption in rural Zimbabwe. Agrekon, 56(1), 67–81. https://doi.org/10.1080/03031853.2017.1283241.
   Web of Science ®Google Scholar
• Mignouna, D. B., Manyong, V. M., Rusike, J., Mutabazi, K. D. S., & Senkondo, E. M. (2011). Determinants of adopting Imazapyr-resistant maize technologies and its impact on household income in western Kenya. AgBioForum, 14(3), 158–163. http://hdl.handle.net/10355/12461.
   Google Scholar
• Moat, J., Williams, J., Baena, S., Wilkinson, T., Demissew, S., Challa, Z. K. T., Gole, T. W., & Davis, A. P. (2017). Coffee farming and climate change in Ethiopia: Impacts, forecasts, resilience and opportunities. Summary report 2017. The strategic climate institutions programme (SCIP). Royal Botanic Gardens, Kew (UK). Pp. 37.
   Google Scholar
• Muluken, G. W., Jemal, Y., Getachew, S. E., Chanyalew, S. A., Dereje, K. M., & Debbebe, T. R. (2021). Adoption of improved agricultural technology and its impact on household income: a propensity score matching estimation in eastern Ethiopia. Agriculture & Food Security, 10, 5. https://doi.org/10.1186/s40066-020-00278-2
   Google Scholar
• Negash, M. (2013). The Indigenous agroforestry systems of the South-Eastern Rift Valley Escarpment, Ethiopia: their biodiversity, carbon stocks, and litterfall. [Doctoral thesis]. Tropical Forestry Reports. No. 44. University of Helsinki.
   Google Scholar
• Perfect Daily Grind. (2020). Africa coffee trade, importing, and exporting. What is the Ethiopian commodity exchange? https://www.google.com/url
   Google Scholar
• Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. https://doi.org/10.1093/biomet/70.1.41
   Web of Science ®Google Scholar
• Samuel, D., & Beza, E. (2019). Impacts of adoption of improved coffee varieties on farmers’ coffee yield and income in Jimma Zone. Agricultural Research & Technology, 21(4), 556169. https://doi.org/10.19080/ARTOAJ.2019.21.556169
   Google Scholar
• Shumete, G. (2009). Proceedings of the 16th International Conference of Ethiopian Studies, Harald Aspen. Poverty, food insecurity and livelihood strategies in rural Gedeo. The case of Haroressa and Chichu PAs, SNNP. In Svein Ege (Ed.), Birhanu Teferra and Shiferaw Bekele, Trondheim 2009.
   Google Scholar
• Solymosi, K., & Techel, G. (2019). Brewing up climate resilience in the coffee sector: Adaptation strategies for farmers, plantations, and producers. Available online at: https://www.idhsustainabletrade.com/uploaded/2019/06/Brewing-up-climate-resilience-in-the-coffee-sector-1.pdf (accessed January 24, 2021).
   Google Scholar
• Southern Nations, Nationalities, and Peoples Region (SNNPR). (2018). Regional overview. FEWSNET, USAID, Disaster Prevention and Preparedness Commission (DPPC), the Government of Ethiopia,
   Google Scholar
• Tollera, M. T. (2020). Ethiopia’s coffee-growing areas may be headed for the hills. Eos, 101. https://doi.org/10.1029/2020EO148824
   Google Scholar
• Tufaa, M., Melese, A., & Tena, W. (2019). Effects of land–use types on selected soil physical and chemical properties: The case of Kuyu District, Ethiopia. Eurasian Journal of Soil Science (Ejss), 8(2), 94–109. https://doi.org/10.18393/ejss.510744
   Google Scholar
• United Nations, Department of Economic and Social Affairs, Population Division (UNDSAPD). (2017). World population prospects: The 2017 revision, Key findings and advance tables. Working Paper No. ESA/P/WP/248.
   Google Scholar
• United States Department of Agriculture (USDA). (2020). Coffee: World markets and trade. https://downloads.usda.library.cornell.edu/usda.smis/files/m900nt40f/sq87c919h/8w32rm91m/coffee.pdf.
   Google Scholar
• World Vision. (2020). Our vision for every child, life in all its fullness; Our prayer for every heart, the will to make it so. Kochore coffee farmer’s co-operatives revitalization support project. Ethiopia.
   Google Scholar
• Wu, F. (2022). Adoption and income effects of new agricultural technology on family farms in China. PloS One, 17(4), e0267101. https://doi.org/10.1371/journal.pone.0267101
   PubMed Web of Science ®Google Scholar
• Zhai, Z., Fuchs, A. L., & Lohmann, I. (2010). Cellular analysis of newly identified Hox downstream genes in Drosophila. European Journal of Cell Biology, 89(2-3), 273–278. https://doi.org/10.1016/j.ejcb.2009.11.012
   PubMed Web of Science ®Google Scholar