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Njoka, J. T., Yanda, P., Maganga, F., Liwenga, E., Kateka, A., Henku, A., Mabhuye, E., Malik, N., & Bavo, C. (2016). Kenya: Country Situation Assessment. Working Paper, Pathways to Resilience in Semi-Arid Economies (PRISE) Project, International Development Research Centre (IDRC).

has been cited by the following article:

• TITLE: Socioeconomic Determinants of Farmers’ Vulnerability to Climate Variability and Extreme Events in Kitui County, Kenya

  AUTHORS: Evelyn J. Mutunga, Charles K. Ndungu, Moses Mwangi, Patrick C. Kariuki

  KEYWORDS: Vulnerability Index, Principal Component Analysis, Multinomial Logistic Regression, Households

  JOURNAL NAME: American Journal of Climate Change, Vol.13 No.4, December 2, 2024

  ABSTRACT: A field survey was carried out to model farmers’ vulnerability to climate variability and extreme events in selected agroecological zones in Kitui County. The indicator approach was used to calculate the overall household vulnerability index, where Principal Component Analysis (PCA) was used to allocate weights to indicators of exposure, sensitivity and adaptive capacity. Multinomial logistic regression was run in Stata to model the influence of socioeconomic characteristics on farmers’ vulnerability levels. The study established that different socioeconomic characteristics of households had a varying influence on the households’ vulnerability levels. Proximity to the Market and the arid agroecological zone significantly reduced the probability of a household belonging to the low and moderate vulnerability categories. On the other hand, the education level and the semi-humid zone significantly increased the odds of a household belonging to the low vulnerability category. Further, access to credit facilities and the semi-humid agroecological zone significantly increased the odds of a household belonging to the moderate vulnerability category. The study thus recommends that policy interventions should target specific socioeconomic characteristics that influence households’ vulnerability to climate variability and extreme events.