Variability in Cross‐Domain Risk Perception among Smallholder Farmers in Mali by Gender and Other Demographic and Attitudinal Characteristics. Issue 7 (15th February 2018)

• Record Type: Journal Article
• Authors: Cullen, Alison C.; Anderson, C. Leigh; Biscaye, Pierre; Reynolds, Travis W.
• Is Part Of: Risk analysis. Volume 38:Issue 7(2018)
• Page Start: 1361
• Page End: 1377
• Publication Date: 2018-02-15
• Subjects: Development -- gender -- Mali -- risk perception -- smallholder farmers; Technology -- Risk assessment -- Periodicals; 658.403
• DOI: 10.1111/risa.12976
• Languages: English
• ISSNs: 0272-4332

Abstract

Abstract: Previous research has shown that men and women, on average, have different risk attitudes and may therefore see different value propositions in response to new opportunities. We use data from smallholder farm households in Mali to test whether risk perceptions differ by gender and across domains. We model this potential association across six risks (work injury, extreme weather, community relationships, debt, lack of buyers, and conflict) while controlling for demographic and attitudinal characteristics. Factor analysis highlights extreme weather and conflict as eliciting the most distinct patterns of participant response. Regression analysis for Mali as a whole reveals an association between gender and risk perception, with women expressing more concern except in the extreme weather domain; however, the association with gender is largely absent when models control for geographic region. We also find lower risk perception associated with an individualistic and/or fatalistic worldview, a risk‐tolerant outlook, and optimism about the future, while education, better health, a social orientation, self‐efficacy, and access to information are generally associated with more frequent worry—with some inconsistency. Income, wealth, and time poverty exhibit complex associations with perception of risk. Understanding whether and how men's and women's risk preferences differ, and identifying other dominant predictors such as geographic region and worldview, could help development organizations to shape risk mitigation interventions to increase the likelihood of adoption, and to avoid inadvertently making certain subpopulations worse off by increasing the potential for negative outcomes.