Application of Probit Analysis in the Decision of Youths to Participate in Vegetable Production
Youths are successor farming generation and therefore the future of food security. At present, they constitute about 60% of Nigeria’s population and have over the years contributed significantly to national development. Unfortunately, the present environment makes it difficult to explore their full potentials in production through participation in agriculture. The ageing smallholder farmers are less likely to increase capacity needed to sustainably expand agricultural production. There is therefore a pressing need to engage the youth in ways that they can see a promising future in agriculture as well as influence them to build capacity through effective involvement in agricultural production. Several factors however, have continued to hinder capacity building and effective participation of youths in vegetable farming. An empirical study was conducted to estimate the factors affecting the willingness of youth to participate in small scale waterleaf production. The representative waterleaf producers were selected using the multi stage sampling procedures.With the aid of questionnaire, primary data were obtained from 100 farmers. Univariate probit regression model was used to analyze the data. Results of analysis indicated that the most critical factors affecting the participation of youths in waterleaf production were age, educational qualification, size of household members, and farm income. Results indicated that youths who have acquired some form of education were more willing to be involved in waterleaf production. Findings further indicated that youth in families with higher income from farming activities were more willing to participate in waterleaf production.
Abdulai, A., & Huffman, W. E. (2005). The diffusion of new agricultural technologies: The case of crossbred-cow technology in Tanzania. American Journal of Agricultural Economics, 87(3), 645-659.
Ahaibwe, G., Mbowa, S. & Mayanja, M. L. (2013). Youth engagement in agriculture in Uganda: Challenges and Prospect. Unpublished Working Paper. Economic Policy Research Centre (EPRC).
Bamire, A. S., & Ayanwale, A. B. (1995). Costs and returns in alternative poultry keeping systems in Southern Nigeria: A comparative analysis. Indian Journal of Economics, 76, 47-60.
Chianu, J. N., & Tsujii, H. (2005). Determinants of farmers’ decision to adopt or not adopt inorganic fertilizer in the savannas of northern Nigeria. Nutrient cycling in agroecosystems, 70(3), 293-301.
Chirwa, E. W. (2005). Adoption of fertiliser and hybrid seeds by smallholder maize farmers in Southern Malawi. Development Southern Africa, 22(1), 1-12.
Etim, N. A. & D. N. Benson (2016). Willingness to Pay for Organic Fertilizer by Resource Poor Vegetable Farmers in the Humid Tropic. Journal of Agriculture and Ecology Research International 6(2):1-11.
Etim, N. A. & Edet G. E. (2014). Efficiency of resource utilization in dry season waterleaf Talinum triangulate Jacq.wild production by women in southern Nigeria. Asian Journal of Agriculture Extension, economic and sociology, 3(2), 138-146.
Etim, N. A. A., & Udoh, E. J. (2018). Willingness of youths to participate in agricultural activities: Implication for poverty reduction. American Journal of Social Sciences, 6(1), 1-5.
Etim, N. A., S. Okon & I. Akpabio (2011). Labour and Poverty: Empirical Relationship using House Data from South Nigeria. International Journal of Agricultural Management and Development, 1(2), 53-59.
Etim, N. A.; D. Thompson & C. E. Onyenweaku (2013). Measuring Efficiency of Yam (Dioscorea spp). Production among Resource Poor Farmers in Uyo, Nigeria. Discourse Journal of Agricultural and Food Sciences, 1(3), 42-47.
Falusi A. O. (1975). Application of Multivariate Probit to fertilizer use decision: Sample survey of farmers in three states in Nigeria. Journal Rural Economic Development, 9(1), 49-66.
Hailu Z. (1990). The adoption of modern farm practices in African agriculture: Empirical Evidence about the impact of household characteristics and input supply systems in the Northern region of Ghana. Nyankpala Agricultural Research Report L71 Ghana. Agricultural Experimental Station, Tamale, Ghana.
Kwenye, J. M. & Sichone, T. (2016). Rural youth participation in Agriculture: Exploring the significance and challenges in the control of agricultural sector in Zambian. RUFORUM Working document Series.
Lapar, M. L. A., & Pandey, S. (1999). Adoption of soil conservation: the case of the Philippine uplands. Agricultural economics, 21(3), 241-256.
Madukwe M. C. (1995). Obstacles to the adoption of yam minisett technology by small-scale farmers of South Eastern Nigeria. Agro Search, 1(1), 1-5.
Maina, W. N., & Maina, F. M. P. (2012). Youth engagement in agriculture in Kenya: Challenges and prospects. Update, 2.
Matthews-Njoku, E. C. (2005). Farmers' Adoption Of Improved Soil Conservation And Management Practices In A Rainforest Zone Of Nigeria. Global Approaches to Extension Practice: A Journal of Agricultural Extension, 1(1), 24-30.
Nkamleu, G. B., & Adesina, A. A. (2000). Determinants of chemical input use in peri-urban lowland systems: bivariate probit analysis in Cameroon. Agricultural systems, 63(2), 111-121.
Nkamleu, G. B. (2007). Modeling farmers’ decisions on integrated soil nutrient management in sub-Saharan Africa: a multinomial logit analysis in Cameroon. In Advances in integrated soil fertility management in sub-Saharan Africa: Challenges and opportunities (pp. 891-904). Springer, Dordrecht.
Nnadi, F. N., & Akwiwu, C. D. (2005). Adoption of improved poultry production practices by rural women in Imo State. Animal Production Research Advances, 1(1).
Nnadi, F. N., & Akwiwu, C. D. (2008). Determinants of youthsparticipation in rural agriculture in Imo State, Nigeria. JApSc, 8(2), 328-333.
National Population Commission. (1991). population census of the Federal Republic of Nigeria: Analytical report at the national level. Lagos, National Population Commission. 290p.
Odendo, M., Obare, G. A., & Salasya, B. (2010). Determinants of the speed of adoption of soil fertility-enhancing technologies in Western Kenya (No. 308-2016-5071).
Ohajianya, D. O., & Onu, D. O. (2005). Adoption of improved maize varieties in Imo State as a two–stage decision process. Global Approaches to Extension Practice: A Journal of Agricultural Extension, 1(1), 91-96.
Rahm, M. R., & Huffman, W. E. (1984). The adoption of reduced tillage: the role of human capital and other variables. American journal of agricultural economics, 66(4), 405-413.
Udoh, E. J. (2005). Technical inefficiency in vegetable farms of humid region: An analysis of dry season farming by urban women in South-South Zone, Nigeria. Journal of Agriculture and Social Sciences, 1(2), 80-85.
Udoh, E. J., & Etim, N. A. (2007). Estimating technical efficiency of waterleaf production in a tropical region. Journal of vegetable science, 12(3), 5-13.
Valerie, L. (2009). Youth in Agriculture; Challenges and Opportunities: Proceedings of the 30th Regular Meeting of the Conference of Heads of Government of the Caribbean Community, 2-5 July. Georgetown, Guyana.
Weir, S., & Knight, J. (2000). Adoption and diffusion of agricultural innovations in Ethiopia: the role of education. University of Oxford, Institute of Economics and Statistics, Centre for the Study of African Economies.
Zegeye, T., Tadesse, B., & Tesfaye, S. (1992). Determinants of Adoption of Improved Maize Technologies in Major Maize Growing Regions of Ethiopia. Enhancing the Contribution of Maize to Food Security in Ethiopia, 5, 125.
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