Determinants of farmers’ adaptation to climate change: A micro level analysis in Ghana

Abstract

This study analyzed socio-economic factors that influence farmers' adaptation to climate change in agriculture. Perceptions regarding long-term changes in climate variables and the rate of occurrence of weather extremes were also investigated. Additionally, farmers' perceived barriers to the use of adaptation practices were identified and ranked. A total of 100 farm-households were randomly selected from four communities in the Lawra district of Ghana and data were collected through semi-structured questionnaires, focused group discussions and field observations. A logistic regression model and weighted average index were used to analyze the data. The results showed that 87 % of respondents perceived a decrease in rainfall amount, while 82 % perceived an increase in temperature over the past 10 years. Results of the weighted average index indicate that dry spell and drought have a higher annual rate of occurrence than flood. Empirical results of the logistic regression model showed that education, household size, annual household income, access to information, credit and membership of farmer-based organization are the most important factors that influence farmers' adaptation to climate change. The main constraints on adaptation include unpredictability of weather, high farm input cost, lack of access to timely weather information and water resources. The policy implication of this study is that governments should mainstream barriers to, and choice factors of, adaptation practices to climate change related projects and programs.

The Effects of Climate Smart Agriculture and Climate Change Adaptation on the Technical Efficiency of Rice Farming—An Empirical Study in the Mekong Delta of Vietnam

“…Firstly, the binary propensity score model was run to investigate rice farmers' preference of CSA participation and climate change adaptation response and to estimate the propensity score as the predicted probability of treatment (see equation (1)). Several previous studies also used the binary logistic model to determine key factors affecting farmers' decisions on adaptation response to climate change [6,28,29] as well as to identify influencing factors on farmers' participation decisions [11,[30][31][32]. The propensity score model is generally described as follows:…”

“…These variables included education level, farming experience, agricultural extension services, belief in climate change, trust in public adaptation, social norm, and geographical settings (e.g., province and access to water source). More educated farmers were reported to affect the choice of climate change adaptation [29,39]. They also suggested that the preference of adaptation choice was positively influenced by access to information (e.g., agricultural extension services).…”

Perceptions on climate change and adaptation strategies among sweet potato farming households in Kwara State, Northcentral Nigeria

“…(1) where: F = frequency; W = weight of each scale; i = weight; WI = weighted index (Adesoji and Famuyiwa, 2010;Devkota et al, 2014;Uddin et al, 2014;Ndamani and Watanabe, 2016). Component (iii) was rated based on the frequency of the farmers who responded to the multiple-response questions on the different adaptation strategies they used.…”

Smallholder Rice Farmers’ Adaptation Capacity to Climate Change in the Bawku Zone of Ghana

“…Although we have gained some general ideas about local adaptation strategies among farmers, other studies found that climate change adaptation actions varied partly due to socio-economic factors and geographical locations [8], [9]. Regional adaptation actions can be effective when adaptation policies better incorporate the adaptive capacity of a farmer or farming community [1], [10]- [12].…”