This article analyzes the vulnerability and resilience levels of farm households in North Shewa, Ethiopia, using a survey of 452 households. Agro ecological based classification was done to analyze vulnerability to cl...This article analyzes the vulnerability and resilience levels of farm households in North Shewa, Ethiopia, using a survey of 452 households. Agro ecological based classification was done to analyze vulnerability to climate change induced shocks. Integrated vulnerability analysis approach was employed to develop indexes for socioeconomic and biophysical indicators. The indicators have been classified into adaptive capacity, exposure and sensitivity to climate change impact. Then Principal Component Analysis was used to compute vulnerability index of each agro ecological zone. The result shows that farmers living in the highland areas were very much vulnerable to natural shocks compared to those living in the lowland area. In order to identify and analyse the determinants of resilience to climate change impacts, ordered probit model was used. Households were classified into three categories based on the time they take to bounce back after natural shocks. The model outputs indicate that farmers with better investment on natural resource management, access to market, better social network, access to credit, preparedness, saving liquid assets, access to irrigation and better level of education exhibited greater level of resilience during and after climate change induced shocks.展开更多
文摘This article analyzes the vulnerability and resilience levels of farm households in North Shewa, Ethiopia, using a survey of 452 households. Agro ecological based classification was done to analyze vulnerability to climate change induced shocks. Integrated vulnerability analysis approach was employed to develop indexes for socioeconomic and biophysical indicators. The indicators have been classified into adaptive capacity, exposure and sensitivity to climate change impact. Then Principal Component Analysis was used to compute vulnerability index of each agro ecological zone. The result shows that farmers living in the highland areas were very much vulnerable to natural shocks compared to those living in the lowland area. In order to identify and analyse the determinants of resilience to climate change impacts, ordered probit model was used. Households were classified into three categories based on the time they take to bounce back after natural shocks. The model outputs indicate that farmers with better investment on natural resource management, access to market, better social network, access to credit, preparedness, saving liquid assets, access to irrigation and better level of education exhibited greater level of resilience during and after climate change induced shocks.
