Modelling climate change awareness heterogeneity among smallholder cereal crop farmers in the semi-arid region of Ghana: A latent class regression approach.

Climate change awareness, characterised as experiential knowledge among food crop farmers, is a fundamental factor influencing their climate-smart adaptation decisions and behaviours. A critical issue in this context is the unobserved heterogeneity in awareness levels, resulting in varying degrees of climate resilience among these farmers. Consequently, understanding the heterogeneity in awareness and the factors that influence it is essential for informing effective climate response policies. To investigate this issue, we utilized a latent class regression model to examine the unobserved heterogeneity in climate change awareness among cereal crop farmers and to identify the key determinants of this variation. Data were collected through a multistage sampling procedure from 300 smallholder cereal crop farmers in the Bolgatanga Municipality of the Upper East Region of Ghana. The model identified three distinct latent classes of awareness: low awareness (33 %), moderate awareness (27 %), and strong awareness (40 %), thus highlighting significant heterogeneity in awareness levels among farmers. The analysis revealed that factors such as sex, age, years of education, farmer association membership, years of farming experience, regular access to extension training and information on climate-related actions and spatial location landmark were significant predictors of climate change awareness heterogeneity among farmers. The results further demonstrated that climate change variability awareness trend as reported by farmers corroborated historical evidence of climate change in the study area. Consequently, policymakers and stakeholders in northern Ghana must consider these variations and their determinants when formulating and implementing climate change adaptation and mitigation strategies.