Adoption of integrated crop-livestock management practices (ICLMPs) among men and women smallholder farmers in Ghana

Abstract

Integrated crop-livestock management practices (ICLMPs) play a vital role in ensuring food security and improved welfare for smallholder households, however, studies that focus on ICLMP adoption in Ghana (including its gender dimension) remain scant. This paper examines gender differences in the drivers and intensity of ICLMP adoption using farm-level data from 638 smallholder farmers in Ghana. Employing Multivariate Probit, Tobit regression models and dominance analytical procedures, we find that adoption of ICLMPs is generally influenced by non-farm income, extension contacts and nativity. While age, credit access, soil fertility, distance to markets, total value of assets and research contacts influence the intensity of ICLMP adoption among the men, intensity of adoption among women farmers is influenced mainly by household size. The dominance analysis showed that being a native of the community/village where one farms had the strongest influence in intensifying ICLMP adoption, with gender differences being evident regarding the relative influence of the other variables. Policies to enhance the adoption of ICLMPs in Ghana could be designed to focus on women farmers who have large farm assets, access to extension and are engaged in non-farm income-generating activities

Keywords:

• Gender
• agricultural technology
• adoption
• integrated crop-livestock management practices
• Ghana

JEL Codes:

• Q10
• Q12
• Q15
• Q18

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 This is a livestock husbandry system where the animals are allowed to go out to feed on their own at the early hours of the day and return to their shed when night falls.

2 Generally, the head of household is interviewed, however, in situations where the head is unavailable or wishes to delegate a member to speak on behalf of the household, information relating to the household head and the entire household are obtained from such representative.

3 The binary or categorical variables were tested with the Chi-square test of ANOVA, while difference in continuous or count variables between the two groups were tested using the t-test.

4 Testing for model specification using the link test, we see that across all models, the _hat and _hatsq are significant and insignificant respectively. This means that we fail to reject the null hypothesis that the model is correctly specified.