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- W2292899872 abstract "This paper integrates the use of statistical and econometric tools to measure the vulnerability level of individual households in western part of Ethiopia. Principal Component Analysis (PCA) was used to develop vulnerability index for individual household so as to classify households depending on their level of vulnerability to climate change impacts and then ordered logistic regression model that employed the output of PCA was used to identify the key determinants of vulnerability to climate change impacts. A survey of 180 households in western Wollega was used to generate household level data. The households were categorized into three levels as: highly vulnerable, vulnerable and less vulnerable. The result found that 47, 16 and 36% of the households were highly vulnerable, vulnerable and lowly vulnerable respectively. Households with fewer dependent family members, more number of farm plots in different locations, diversified crops grown, having different types of livestock ownership, having better level of conservation practices on farmlands, access to financial services during critical seasons, and led by a male household head were relatively less vulnerable to climate change impacts as compared to their counterparts." @default.
- W2292899872 created "2016-06-24" @default.
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- W2292899872 date "2013-01-01" @default.
- W2292899872 modified "2023-09-26" @default.
- W2292899872 title "Individual level vulnerability to climate change impact among crop dependent communities of western Ethiopia" @default.
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