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Assessing the adoption rates of improved technology in traditional poultry farming: evidence from rural Togo

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  • Soviadan, Mawussi Kossivi
  • Kubik, Zaneta
  • Enete, Anselm Anibueze
  • Okoye, Chukwuemeka Uzoma

Abstract

The adoption of improved agricultural technologies is known to significantly improve incomes, create more wealth, alleviate poverty, and contribute to rural development in many developing countries. The Government of Togo, through the National Programme for Agricultural Investment and Food Security (PNIASAN) and the Agricultural Sector Support Project (PASA), with financial support from the World Bank and help from the Food and Agriculture Organization of the United Nations (FAO), assist smallholder farmers in improved technology adoption in traditional poultry farming (ITTPF) for wealth creation, food security, and poverty alleviation. However, for any technology or emerging agricultural practices, awareness and exposure are necessary for adoption. And because these two factors are not distributed randomly in the population of potential adopters, not taking them into account will lead to estimates of population adoption rates that are not informative of the actual demand for the technology and inconsistent estimates of the parameters of the adoption model. In this study, we evaluate the adoption rates of ITTPF among farmers in Togo. Data was collected from 400 farmers in 2014, before the introduction of ITTPF, and again five years later. This data was then analyzed using inverse propensity score weighting and parametric estimation of adoption regression models. The results of the estimates indicate that the average treatment effect (𝐴𝑇𝐸), which represents the mean potential adoption rate of the population, is 57%, the average treatment effect on the treated (𝐴𝑇𝐸𝑇), which represents the mean potential adoption rate in the exposed subpopulation, is 60%, the population mean joint exposure and adoption rate (𝐽𝐸𝐴) is 13%, and the population selection bias (𝑃𝑆𝐡) is 3%. The sample adoption rate (𝐽𝐸𝐴) implies a population adoption gap of -47% due to a lack of exposure and adoption by a sufficient population size. The 𝑃𝑆𝐡 is insignificant and indicates that all the sampled farmers had an almost equal opportunity to adopt ITTPF. The study reveals that the sample adoption rate does not consistently estimate the actual population adoption rate. Hence, controlling for non-exposure and selection biases is a prerequisite to acquiring consistent estimates of ITTPF adoption rates. The findings indicate a relatively high supply-demand gap for ITTPF that justifies investment in its further dissemination and adoption in Togo for optimal positive impact on potential outcomes and the welfare of farmers.

Suggested Citation

  • Soviadan, Mawussi Kossivi & Kubik, Zaneta & Enete, Anselm Anibueze & Okoye, Chukwuemeka Uzoma, 2022. "Assessing the adoption rates of improved technology in traditional poultry farming: evidence from rural Togo," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 17(3), pages 206-223.
    • Handle: RePEc:zbw:espost:301788
    DOI: 10.53936/afjare.2022.17(3).14
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    1. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    2. Feder, Gershon & Just, Richard E & Zilberman, David, 1985. "Adoption of Agricultural Innovations in Developing Countries: A Survey," Economic Development and Cultural Change, University of Chicago Press, vol. 33(2), pages 255-298, January.
    3. Yonas Alem, 2015. "Poverty Persistence and Intra-Household Heterogeneity in Occupations: Evidence from Urban Ethiopia," Oxford Development Studies, Taylor & Francis Journals, vol. 43(1), pages 20-43, March.
    4. Ariel Ortiz-Bobea & Toby R. Ault & Carlos M. Carrillo & Robert G. Chambers & David B. Lobell, 2021. "Anthropogenic climate change has slowed global agricultural productivity growth," Nature Climate Change, Nature, vol. 11(4), pages 306-312, April.
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