Fertiliser adoption and sustainable rural livelihood improvement in Nigeria

Research output: Contribution to journalArticlepeer-review

Abstract

Poor soil fertility emanating from land degradation is one of the causes of low crop productivity in Sub-Saharan Africa. Therefore, the issues of food insecurity and poverty have become prevalent in these countries. It is however imperative to explore agricultural innovations such as mineral fertiliser to improve soil fertility of the arable lands in Africa including Nigeria. In this study, we analyse the adoption of mineral fertiliser and its economic impacts on the livelihoods of 400 rural farmers in Nigeria. We apply the endogenous switching regression and propensity score matching approaches in the empirical analyses. We find that the adoption of mineral fertiliser increases cassava yields and net revenues of rural farmers. The enhanced cassava yields and net revenues have implications on the transformation of rural economy by reducing food insecurity, minimising poverty, and improving the overall well-being of rural farmers. The results also show that farmer age and leasing negatively influence the adoption of fertiliser whereas farmer education, experience in cassava farming, household size, keeping of farm record, location differential, access to credit, membership of farmer association, and herbicides show positive effects. To achieve higher adoption of fertiliser among rural farmers, we recommend that agricultural policies could target the aforementioned key factors.

Original languageEnglish
Article number104193
JournalLand Use Policy
Volume88
DOIs
Publication statusPublished - Nov 2019

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 1 - No Poverty
    SDG 1 No Poverty
  2. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger
  3. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  4. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Keywords

  • Endogenous switching regression
  • Livelihood improvement
  • Nigeria
  • Propensity score matching
  • Rural development
  • Technology adoption

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