Vol. 116 No. 2 (2022)
Research Papers

Determinants of Farmers' Participation in the Agricultural Sector Support Project for the Adoption of Improved Technology in Traditional Poultry Farming: Evidence from Rural Togo

Mawussi Kossivi Soviadan
Department of Agricultural Economics, Faculty of Agriculture, University of Nigeria, Nigeria
Anselm Anibueze Enete
Department of Agricultural Economics, Faculty of Agriculture, University of Nigeria, Nigeria
Chukwuemeka Uzoma Okoye
Department of Agricultural Economics, Faculty of Agriculture, University of Nigeria, Nigeria
Zaneta Kubik
Center for Development Research (ZEF), University of Bonn, 53113 Bonn, Germany
Published January 20, 2023
Keywords
  • Traditional poultry farming,
  • Improved technology,
  • Determinants,
  • Adoption,
  • Agricultural cooperative membership,
  • Togo
  • ...More
    Less
How to Cite
Soviadan, M. K., Enete, A. A., Okoye, C. U., & Kubik, Z. (2023). Determinants of Farmers’ Participation in the Agricultural Sector Support Project for the Adoption of Improved Technology in Traditional Poultry Farming: Evidence from Rural Togo. Journal of Agriculture and Environment for International Development (JAEID), 116(2), 87-108. https://doi.org/10.36253/jaeid-12642

Abstract

The adoption of improved technologies in agriculture has been shown to improve incomes, reduce poverty and contribute to rural development in many developing nations. In Togo, the Agricultural Sector Support Project (PASA) assists smallholder farmers in the adoption of the Improved Technology in Traditional Poultry Farming (ITTPF) in rural areas as a means of increasing smallholder incomes, enhancing food security and reducing poverty. However, the adoption rate is currently below expectations, especially given the promise it holds not only from an economic perspective but also from a broad environmental sustainability viewpoint since poultry manure can be used as a necessary input in smallholder farms. In this study, we examine the factors associated with the participation of farmers in PASA for the adoption of ITTPF in Togo. Our analysis covers 400 smallholder households in the 23 districts of Togo and employs Logit model with Probit model as robustness check. We find different socio-economic constraints and enablers of participation in PASA. Particularly, level of education, household size, membership in cooperative societies, hatching rate of eggs, farm size, average annual sale of poultry and self-financing capacity were positively and significantly related to the participation of farmers in PASA. The findings are robust to alternative specifications such as Probit model. Based on the findings, we argue that participation in agricultural innovation and development programs depends on the information accessible to farmers. One medium to improve information access could be agricultural cooperatives and extension services since they provide informal education, training, and access to productive inputs for farming and marketing purposes. Our findings suggest the need for agricultural policies which promote farmer organizations such as agricultural cooperatives coupled with effective extension services to enable the adoption of improved agricultural technologies.

References

  1. Afolayan, O. S. 2021. Local and scientific methods of soil fertility assessment in the tropics: a review. African Geographical Review, DOI: 10.1080/19376812.2021.1920435
  2. Ajates, R. 2020. An integrated conceptual framework for the study of agricultural cooperatives: from repolitisation to cooperative sustainability. Journal of Rural Studies, 78 (August), 467–479. https://doi.org/10.1016/j.jrurstud.2020.06.019
  3. Akpaden, I., Enin, M., State, A. I., Akpaeti, A. J., and Udo, U. J. 2014. Labour Choice Decisions Among Cassava Crop Farmers in Akwa Ibom State , Nigeria. Department of Agricultural Economics and Resources Management Akwa Ibom. International Journal of Food and Agricultural Economics ISSN 2147-8988, (23), 145–156.
  4. Akudugu, M. A., Guo, E., and Dadzie, S. K. 2012. Adoption of Modern Agricultural Production Technologies by Farm Households in Ghana: What Factors Influence their Decisions? Journal of Biology, Agriculture and Healthcare, 2(3), 1–13.
  5. Albert, A., Hepelwa, A., Yami, M., and Manyong, V. 2020. Assessment of Factors Influencing Youth Involvement in Horticulture Agribusiness in Tanzania : A Case Study of Njombe Region. Agriculture, 10 (287), 1–17. https://doi.org/10.3390/agriculture10070287
  6. Aldrich, J. H., Nelson, F. D., and Adler, E. S. 1984. Linear Probability, Logit, and Probit Models. Sage Publication. The International Professional Publishers. (07-045)
  7. Alem, Y. 2015. Poverty Persistence and Intra-Household Heterogeneity in Occupations: Evidence from Urban Ethiopia. Oxford Development Studies, 43(1), 20–43. https://doi.org/10.1080/13600818.2014.944123
  8. Alem, Y., and Broussard, N. H. 2018. The impact of safety nets on technology adoption: a difference-in-differences analysis. Agricultural Economics (United Kingdom), 49(1), 13–24. https://doi.org/10.1111/agec.12392
  9. Ali, E. 2021. Farm Households’ Adoption of Climate-smart Practices in Subsistence Agriculture: Evidence from Northern Togo. Environmental Management, 67(5), 949–962. https://doi.org/10.1007/s00267-021-01436-3
  10. Amemiya, T. 1977. Economics Department of the University of Pennsylvania Institute of Social and Economic Research -- Osaka University. International Economic Review, 4(2), 693–709. https://doi.org/10.1080/00420986820080431
  11. Angrist, J. and Pischke, J. 2008. Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. https://doi.org/10.1515/9781400829828
  12. Awotide, B. A., Karimov, A. A., and Diagne, A. 2016. Agricultural technology adoption, commercialization and smallholder rice farmers’ welfare in rural Nigeria. Agricultural and Food Economics, 4(1). https://doi.org/10.1186/s40100-016-0047-8
  13. Benin, S., and Yu, B. (2012). Complying with the Maputo Declaration Target: Trends in public agricultural expenditures and implications for pursuit of optimal allocation of public agricultural spending. ReSAKSS Annual Trends and Outlook Report.
  14. Bliss, C., and Fisher, R. 1935. Probit model, 1–4
  15. Boote, K.J., Adesogan, A.T., Balehegn, M., Duncan, A., Muir, J.P., Dubeux, J.C., Jr. and Rios, E.F. 2021. Fodder development in Sub-Saharan Africa: An Introduction. Agronomy Journal. https://doi.org/10.1002/agj2.20924
  16. Brooks, C. 2008. Introductory. Econometrics for Finance. Cambridge University, Cambridge. https://doi.org/https://doi.org/10.1017/CBO9780511841644
  17. Carrasco, J. A., and De Dios Ortuzar, J. 2002. Review and assessment of the nested Logit model. Transport Reviews, 22(2), 197–218. https://doi.org/10.1080/01441640110091224
  18. Conley, T. G., and Udry, C. R. 2010. Learning about a new technology: Pineapple in Ghana. American Economic Review, 100(1), 35–69. https://doi.org/10.1257/aer.100.1.35
  19. Coulibaly-Lingani, P., Savadogo, P., Tigabu, M., and Oden, P. C. 2011. Factors influencing people’s participation in the forest management program in Burkina Faso, West Africa. Forest Policy and Economics, 13(4), 292–302. https://doi.org/10.1016/j.forpol.2011.02.005
  20. Cramer, J. S. 2004. The early origins of the Logit model. Studies in History and Philosophy of Science Part C :Studies in History and Philosophy of Biological and Biomedical Sciences, 35(4), 613–626. https://doi.org/10.1016/j.shpsc.2004.09.003
  21. Curry, G. N., Nake, S., Koczberski, G., Oswald, M., Rafflegeau, S., Lummani, J., Peter, E., and Nailina, R. 2021. Disruptive innovation in agriculture: Socio-cultural factors in technology adoption in the developing world. Journal of Rural Studies. https://doi.org/10.1016/j.jrurstud.2021.07.022
  22. Dao, B. 2010. Recensement (qualitatif/quantitatif) de toutes les exploitations avicoles et des structures de la filière dans toutes les régions du pays.
  23. Rapport FAO/OSRO/TOG/801/EC, 36p.
  24. Devendra, C., and Chantalakhana, C. 2002. Animals, poor people and food insecurity: Opportunities for improved livelihoods through efficient natural resource management. Outlook on Agriculture, 31(3), 161–175. https://doi.org/10.5367/000000002101294010
  25. Dubin J. A. and Rivers D. 1989. Selection Bias in Linear Regression, Logit and Probit Models. Sociological Methods and Research, Sage Publications, 18 (2and3), 360-390
  26. Duflo, E., Kremer, M., and Robinson, J. 2011. Nudging farmers to use fertilizer: Theory and experimental evidence from Kenya. American Economic Review, 101(6), 2350–2390. https://doi.org/10.1257/aer.101.6.2350
  27. Dupas, P. 2014. Short-Run Subsidies and Long-Run Adoption of New Health Products: Evidence From a Field Experiment. Econometrica, 82(1), 197–228. https://doi.org/10.3982/ecta9508
  28. ECOWAS. 2005. Memorandum on the Challenges of the Agricultural Sector in ECOWAS Foreign Trade Policy. Implications for the Negotiation of the Economic Partnership Agreement with the European Union. https://www.alimenterre.org
  29. Enamul Haque, A. K., Mukhopadhyay, P., Nepal, M., and Shammin, M. R. (Eds.). 2022. Change and Community Resilience. Springer, Singapore. https://doi.org/https://doi.org/10.1007/978-981-16-0680-9
  30. Enete, A. A., and Amusa, T. A. 2010. Determinants of women’s contribution to farming decisions in cocoa based agroforestry households of Ekiti, State, Nigeria. Field Actions Science Reports, 4(October 2012), 241–254.
  31. FAO. 2014a. Decision tools for family poultry development. FAO Animal Production and Health Guidelines (Vol. 16).
  32. FAO. 2014b. Family poultry development-Issues, opportunities and constraints. Animal Production and Health Working Paper. No. 12. Rome.
  33. Fellegi, I. P. 2003. Méthode et pratiques d’enquêtes. N° 12-587-X au catalogue. Ottawa, Canada.
  34. Gauthier, J., and Langlois, A.-M. 2010. Programme National d’Investissement Agricole et de Sécurité Alimentaire: PNIASA. Plan d’investissement 2010-2015. Lomé-Togo.
  35. Giller, K. E. 2020. The Food Security Conundrum of sub-Saharan Africa. Global Food Security, 26(July), 100431. https://doi.org/10.1016/j.gfs.2020.100431
  36. Giné, X., Townsend, R., and Vickery, J. 2008. Patterns of rainfall insurance participation in rural India. World Bank Economic Review, 22(3), 539–566. https://doi.org/10.1093/wber/lhn015
  37. Greene, W.H. 2012. Econometric Analysis. https://doi.org/10.4337/9781781000915.00021
  38. Grimm, M., Munyehirwe, A., Peters, J., and Sievert, M. 2017. A first step up the energy ladder? Low cost solar kits and household’s welfare in rural Rwanda. World Bank Economic Review, 31(3), 631–649. https://doi.org/10.1093/wber/lhw052
  39. Gujarati, D., and Porter, D. (2009). Basic Econometrics 4ed. The McGraw-Hill Companies. International Edition
  40. Gujarati, D., and Porter, D. 2009. Essentials of Econometrics 4e. McGraw Hill
  41. Haile, D., Seyoum, A., and Azmeraw, A. 2021. Does building the resilience of rural households reduce multidimensional poverty? Analysis of panel data in Ethiopia. Scientific African, 12, e00788. https://doi.org/10.1016/j.sciaf.2021.e00788
  42. Heckman, J. J., and Macurdy, T. E. 1985. A Simultaneous Equations Linear Probability Model. The Canadian Journal of Economics, 18(1), 28. https://doi.org/10.2307/135111
  43. Hübel, C., and Schaltegger, S. 2021. Barriers to a sustainability transformation of meat production practices - An industry actor perspective. Sustainable Production and Consumption, 29, 128–140. https://doi.org/10.1016/j.spc.2021.10.004
  44. IPCC. 2007. Climate Change 2007. Impacts, Adaptation and Vulnerability. Working Group II Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. 978 0521 88010-7 Hardback, 978 0521 70598-1 Paperback.
  45. Issahaku, G., Abdul-Rahaman, A., and Amikuzuno, J. 2021. Climate change adaptation strategies, farm performance and poverty reduction among smallholder farming households in Ghana. Climate and Development, 13(8), 736–747. https://doi.org/10.1080/17565529.2020.1860884
  46. Kolavalli, S. 2010. Do Comprehensive Africa Agriculture Development Program (CAADP) Processes Make a Difference to Country Commitments to Develop Agriculture?
  47. Kolavalli, S., Birner, R., and Flaherty, K. 2012. The Comprehensive Africa Agriculture Program as a Collective Institution. International Food Policy Research Institute (IFPRI).
  48. Kondombo, S. R., Nianogo, A. J., Kwakkel, R. P., Udo, H. M. Y., and Slingerland, M. 2003. Comparative analysis of village chicken production in two farming systems in Burkina Faso. Tropical Animal Health and Production 35: 563- 574.
  49. Konja, D. T. 2021. Technology Adoption and Output Difference Among Groundnut Farmers in Northern Ghana. European Journal of Development Research, 0123456789. https://doi.org/10.1057/s41287-021-00372-6
  50. Laurett, R., Paço, A., and Mainardes, E. W. 2021. Sustainable Development in Agriculture and its Antecedents, Barriers and Consequences – An Exploratory Study. Sustainable Production and Consumption, 27, 298–311. https://doi.org/10.1016/j.spc.2020.10.032
  51. Liu, Y., Wood, L. C., Venkatesh, V. G., Zhang, A., and Farooque, M. 2021. Barriers to sustainable food consumption and production in China: A fuzzy DEMATEL analysis from a circular economy perspective. Sustainable Production and Consumption, 28, 1114–1129. https://doi.org/10.1016/j.spc.2021.07.028
  52. Manda, J., Alene, A. D., Gardebroek, C., Kassie, M., and Tembo, G. 2020. Adoption and Impacts of Sustainable Agricultural Practices on Maize Yields and Incomes: Evidence from Rural Zambia. Journal of Agricultural Economics, 67(1), 130–153. https://doi.org/10.1111/1477-9552.12127
  53. Menghistu, H. T., Zenebe Abraha, A., Mawcha, G. T., Tesfay, G., Mersha, T. T., and Redda, Y. T. 2021. Greenhouse gas emission and mitigation potential from livestock production in the drylands of Northern Ethiopia. Carbon Management, 12(3), 289–306. https://doi.org/10.1080/17583004.2021.1921620
  54. Mensah, H., Ahadzie, D. K., Takyi, S. A., and Amponsah, O. 2021. Climate change resilience: lessons from local climate-smart agricultural practices in Ghana. Energy, Ecology and Environment, 6(3), 271–284. https://doi.org/10.1007/s40974-020-00181-3
  55. Mng’ong’o, M., Munishi, L. K., Blake, W., Comber, S., Hutchinson, T. H., and Ndakidemi, P. A. 2021. Soil fertility and land sustainability in Usangu Basin-Tanzania. Heliyon, 7(8), e07745. https://doi.org/10.1016/j.heliyon.2021.e07745
  56. Mogaka, B. O., Bett, H. K., and Ng’ang’a, S. K. 2021. Socioeconomic factors influencing the choice of climate-smart soil practices among farmers in western Kenya. Journal of Agriculture and Food Research, 5, 100168. https://doi.org/10.1016/j.jafr.2021.100168
  57. NDC. 2021. Updated Nationally Determined Contribution. In Federal Democratic Republic of Ethiopia.
  58. NDP. 2018. National Development Plan in Togo. 2018-2022.
  59. Neupane, R. P., Sharma, K. R., and Thapa, G. B. 2002. Adoption of agroforestry in the hills of Nepal: A logistic regression analysis. Agricultural Systems, 72(3), 177–196. https://doi.org/10.1016/S0308-521X(01)00066-X
  60. OECD/FAO. 2020. OECD-FAO Agricultural Outlook 2020-2029. In FAO, Rome/OECD Publishing, Paris. https://doi.org/10.1787/1112c23b-en
  61. Omara, H., Odongo, W., and Kule, E. K. 2021. Adoption of environmentally friendly agricultural technologies among smallholder farmers: The case of rocket barn technology in flue-cured tobacco curing in Uganda. Land Degradation and Development, 32(2), 965–974. https://doi.org/10.1002/ldr.3765
  62. Ortiz-Bobea, A., Ault, T. R., Carrillo, C. M., Chambers, R. G., and Lobell, D. B. 2021. Anthropogenic climate change has slowed global agricultural productivity growth. Nature Climate Change, 11(4), 306–312. https://doi.org/10.1038/s41558-021-01000-1
  63. Ortmann, G. F., and King, R. P. 2007. Agricultural cooperatives I: History, theory and problems. Agrekon, 46(1), 18–46. https://doi.org/10.1080/03031853.2007.9523760
  64. Ouédraogo, M. 2012. Impact des changements climatiques sur les revenus agricoles au Burkina Faso. Journal of Agriculture and Environment for International Development, 106(1), 3–21.
  65. Peles, S. B., and Kerret, D. 2021. Sustainable technology adoption by smallholder farmers and goal-oriented hope. Climate and Development, 0(0), 1–10. https://doi.org/10.1080/17565529.2021.1872477
  66. Qi, X., Liang, F., Yuan, W., Zhang, T., and Li, J. 2021. Factors influencing farmers’ adoption of eco-friendly fertilization technology in grain production: An integrated spatial–econometric analysis in China. Journal of Cleaner Production, 310(1), 127536. https://doi.org/10.1016/j.jclepro.2021.127536
  67. ROPPA. 2013. Ten Years After the Maputo Declaration on Agriculture and Food Security: An Assessment of Progress in West Africa: CASE OF TOGO. In European Centre for Development Policy Management. https://www.roppa-afrique.org/IMG/pdf/togo _rapport_final-kf.pdf
  68. Roy, R., Gain, A. K., Hurlbert, M. A., Samat, N., Tan, M. L., and Chan, N. W. 2021. Designing adaptation pathways for flood-affected households in Bangladesh. Environment, Development and Sustainability, 23(4), 5386–5410. https://doi.org/10.1007/s10668-020-00821-y
  69. Selejio, O., and Lasway, J. A. 2019. Economic analysis of the adoption of inorganic fertilisers and improved maize seeds in Tanzania. African Journal of Agricultural and Resource Economics, 14(4), 310–330.
  70. Sisha, T. A. 2020. Household level food insecurity assessment: Evidence from panel data, Ethiopia. Scientific African, 7. https://doi.org/10.1016/j.sciaf.2019.e00262
  71. Soviadan M.K., Enete A.A., Okoye C.U. and Dossa K.F. 2021. Extensive and Improved Traditional Poultry Farming in Togo: A Comparative Analysis of Socioeconomic Characteristics of Farmers. European Scientific Journal, ESJ, 17 (35), 274. https://doi.org/10.19044/esj.2021.v17n35p274
  72. Soviadan, M. K., Koffi-Tessio, E. M., Enete, A. A., and Nweze, N. J. 2019. Impact of Climate Change on Cotton Production: Case of Savannah Region, Northern Togo. Agricultural Sciences, 10(07), 927–947. https://doi.org/10.4236/as.2019.107071
  73. Stoltzfus, J. C. 2011. Logistic Regression : A Brief Primer. Academic Emergency Medicine, 18(10), 1099–1104. https://doi.org/10.1111/j.1553-2712.2011.01185.x
  74. Tamimie, C. A., and Goldsmith, P. D. 2019. Determinants of soybean adoption and performance in Northern Ghana. African Journal of Agricultural and Resource Economics, 14(4), 292–309.
  75. Tesfaye, T., Sithole, B., and Ramjugernath, D. 2017. Valorisation of chicken feathers: a review on recycling and recovery route—current status and future prospects. In Clean Technologies and Environmental Policy (Vol. 19, Issue 10, pp. 2363–2378). Springer Berlin Heidelberg. https://doi.org/10.1007/s10098-017-1443-9
  76. Tesfaye, T., Sithole, B., Ramjugernath, D., and Chunilall, V. 2017. Valorisation of chicken feathers: Application in paper production. Journal of Cleaner Production, 164, 1324–1331. https://doi.org/10.1016/j.jclepro.2017.07.034
  77. Tey, Y. S., and Brindal, M. 2012. Factors influencing the adoption of precision agricultural technologies: A review for policy implications. Precision Agriculture, 13(6), 713–730. https://doi.org/10.1007/s11119-012-9273-6
  78. Tobogbonse, E.B, Jibrin, M.M, Auta, S.J and Damisa, M. 2013. Factors influencing women participation in Women In Agriculture (WIA) Programme of Kaduna State Agricultural Development Project , Nigeria. International Journal of Agricultural Economics and Extension, 1(7), 47–54.
  79. Toldrá, F., Mora, L., and Reig, M. 2016. New insights into meat by-product utilization. Meat Science, 120, 54–59. https://doi.org/10.1016/j.meatsci.2016.04.021
  80. Tuck, C. O., Pérez, E., Horváth, I. T., Sheldon, R. A., and Poliakoff, M. 2012. Valorization of biomass: Deriving more value from waste. Science, 337(6095), 695–699. https://doi.org/10.1126/science.1218930
  81. Tui, S. H. K., Descheemaeker, K., Valdivia, R. O., Masikati, P., Sisito, G., Moyo, E. N., Crespo, O., Ruane, A. C., and Rosenzweig, C. 2021. Climate change impacts and adaptation for dryland farming systems in Zimbabwe: a stakeholder-driven integrated multi-model assessment. Climatic Change, 168(1–2). https://doi.org/10.1007/s10584-021-03151-8
  82. UN-DESA-PD. 2019. United Nations, Department of Economic and Social Affairs, Population Division. Volume II: Demographic Profiles (ST/ESA/SER.A/427). In World Population Prospects 2019.
  83. UNDP. 2011. L’impact des changements climatiques : analyse des volets relatifs à la pauvreté au Togo. Rapport final. 66.
  84. Williamson, O. E. 2000. The new institutional economics: Taking stock, looking ahead. Journal of Economic Literature, 38(3), 595–613. https://doi.org/10.1257/jel.38.3.595
  85. Wooldridge, J. M. 2003. Econometric Analysis of Cross Section and Panel Data. MIT Press, 16(4), 369–412. https://doi.org/10.1515/humr.2003.021
  86. Wooldridge, J. M. 2005. Introductory Econometrics. A Modern Approach. Nelson Education
  87. World-Bank. 2017. International Development Association. Project paper on a proposed additional credit in an amount equivalent to Euro 18.7 Million (US $ 20 Million equivalent) to the Republic of Togo for the Agricultural Sector Support Project. Report No: PAD2219.
  88. Xie, H., and Huang, Y. 2021. Influencing factors of farmers’ adoption of pro-environmental agricultural technologies in China: Meta-analysis. Land Use Policy, 109(June), 105622. https://doi.org/10.1016/j.landusepol.2021.105622
  89. Zhang, C., Robinson, D., Wang, J., Liu, J., Liu, X., and Tong, L. 2011. Factors influencing farmers’ willingness to participate in the conversion of cultivated land to wetland Program in Sanjiang National Nature Reserve, China. Environmental Management, 47(1), 107–120. https://doi.org/10.1007/s00267-010-9586-z
  90. Zhang, S., Sun, Z., Ma, W., and Valentinov, V. 2019. The effect of cooperative membership on agricultural technology adoption in Sichuan, China. China Economic Review, 62(2), 1–15. https://doi.org/10.1016/j.chieco.2019.10133
  91. Zubir, M. A., Bong, C. P. C., Ishak, S. A., Ho, W. S., and Hashim, H. 2021. The trends and projections of greenhouse gas emission by the livestock sector in Malaysia. Clean Technologies and Environmental Policy, 0123456789. https://doi.org/10.1007/s10098-021-02156-2