The determinants of livelihood diversification among small-scale rural farmers in Alfred Nzo and King Cetshwayo District, South Africa

Abstract

The determinants of livelihood diversification have been studied by several researchers globally. However, these factors are not well understood in the ANDM and KCDM, because they are given little attention. The specific objective of the study was to examine the determinants of livelihood diversification in ANDM and KCDM. The cross-sectional dataset was collected from 268 and 264 participants who were randomly selected in ANDM and KCDM, respectively. A structured questionnaire was utilized to collect data on socio-economic and demographic factors among small-scale rural farmers in ANDM and KCDM. The data collection commenced in March to April 2022 in KCDM and started in August to September 2022 in ANDM. Stata version 14.0 was employed to estimate a Quantile regression. The results show that 66.04% of participants in ANDM were female-headed households, whereas 53.79% in KCDM were headed by males. The findings from a Quantile regression show that livelihood diversification was influenced by the household head's gender, age, marital status, access to extension services, access to credit, employment status, food security, education, household size, farm size, poverty status, farm experience, and improved seeds. To promote livelihood diversification, policymakers should create policies that will target all factors that are significant in the study. The determinants of livelihood diversification have been explored by researchers on a global scale. However, these factors are not well recognized in the ANDM and KCDM regions as they are given little attention. The primary focus of the study was to analyze the determinants of livelihood diversification in ANDM and KCDM. A Quantile regression show that livelihood diversification was influenced by the household head's gender, age, marital status, access to extension services, access to credit, employment status, food security, education, household size, farm size, poverty status, farm experience, and improved seeds. To enhance livelihood diversification, policymakers should design policies that focus on all significant factors outlined in the study.