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Do ICT based extension services improve technology adoption and welfare? Empirical evidence from Ghana

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  • Sadick Mohammed
  • Awudu Abdulai

Abstract

This paper examines the impact of ICT-based extension services on farmers’ adoption of a new agricultural technology (Bradyrhizobium inoculant), knowledge gain on the new technology, yields and net returns, using recent survey data of 600 soybean farmers from Ghana. We employ a copula functions approach to account for potential selection bias and endogeneity. Standard selectivity correction models often employed in the literature rely on multivariate normality (MVN) assumption, which is easily violated, especially when there is tail dependence in the distribution of the observed data, thus making the distribution non-normal. The copula functions approach allows the modelling of selectivity based on multivariate non-normality to account for this deficit in the data, but retains the MVN as a special case. Our empirical findings reveal that farmers who participated in ICT-based extension obtained 205% knowledge scores, 151% yields and 88% farm net returns, compared to 174% knowledge scores, 148% yields and 86% farm net returns for conventional extension participants. The current study provides evidence that employing ICT-based extension delivery to farmers can help in accelerating progress towards the achievement of the Sustainable Development Goals, particularly goals two and five, which seek to achieve zero hunger and equalaccess to extension services.

Suggested Citation

  • Sadick Mohammed & Awudu Abdulai, 2022. "Do ICT based extension services improve technology adoption and welfare? Empirical evidence from Ghana," Applied Economics, Taylor & Francis Journals, vol. 54(23), pages 2707-2726, May.
  • Handle: RePEc:taf:applec:v:54:y:2022:i:23:p:2707-2726
    DOI: 10.1080/00036846.2021.1998334
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    Cited by:

    1. Sadick Mohammed & Awudu Abdulai, 2022. "Do Egocentric information networks influence technical efficiency of farmers? Empirical evidence from Ghana," Journal of Productivity Analysis, Springer, vol. 58(2), pages 109-128, December.

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