Determinants of livelihood diversification in rural rain-fed region of Pakistan: evidence from fractional multinomial logit (FMLOGIT) estimation

Environ Sci Pollut Res Int. 2023 Jan;30(5):13185-13196. doi: 10.1007/s11356-022-23040-6. Epub 2022 Sep 20.

Abstract

Sustainable livelihoods in less developed countries are threatened by human, natural, physical, social and financial factors. Pakistan is also facing severe negative impacts of these factors in the form of climate shocks, market imperfections and insufficient formal credit availability on rural livelihoods. This study explores rural Pakistani's adaptation to these threats by diversifying income sources and explores the determining factors for adopting specific livelihood diversification strategies. The study is based on a quantitative survey of 295 households in three districts of rain-fed rural regions of Pakistan's Punjab with differing annual rainfall. Results showed that households mitigated against threats to their livelihood by having a diversity of income sources (Simpson Diversity Index = 0.61). Moreover, fractional multinomial regression modelling revealed that greater education was associated with a more diversified livelihood strategy, where income was predominantly derived from off-farm and non-farm livelihood activities. On the other hand, households with older members, more livestock and larger farm size focused their livelihoods on their own farms, or primarily diversified into an off-farm strategy by working on other farms. These findings underscore the importance of improved access to education and infrastructure for livelihood diversification. A policy that focuses on reducing low literacy rates in rural Pakistan may also provide new avenues of livelihood diversifications with enhancement of rural literacy rate to mitigate the risks associated with livelihood strategies of smallholders.

Keywords: Fractional multinomial logit; Livelihood capitals; Livelihood diversification strategies; Pakistan.

MeSH terms

  • Agriculture*
  • Farms
  • Humans
  • Income*
  • Pakistan
  • Rain