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dc.contributor.authorKariuki, George
dc.contributor.authorNjaramba, Jennifer
dc.contributor.authorOmbuki, Charles
dc.date.accessioned2018-10-23T06:40:49Z
dc.date.available2018-10-23T06:40:49Z
dc.date.issued2018-04
dc.identifier.isbn978-9966-117-37-3
dc.identifier.urihttp://ir.mksu.ac.ke/handle/123456780/752
dc.description.abstractThe agricultural sector plays a critical role in the Kenyan economy in terms of employment and food security. However, the sector and particularly crop farming is vulnerable to climate change, given that rain fed agriculture accounts for approximately 98 percent of agricultural activities. Crop farming in Kenya has limited diversification and maize production iscritical. Maize production forms a strong base to food security, employment, income generation, poverty alleviation, as well as economic growth and development. This notwithstanding, maize production has greatly fluctuated leaving about 40 percent of population food insecure. Maize production largely depends on climate variables and is highly sensitive to climate change. Thus, it is important to understand the effects of the changing temperature and rainfall patterns, to which this study contributes by analyzing the marginal effects of climate change on maize yield. The study adopted an econometric modeling approach using data for the period between 1970 and 2014. The study findings show that climate change has adverse effects on maize yield. In addition, the study finds a nonlinear relationship between maize yield and climatic variables. However, the direction and magnitude of the effects vary depending on the season. Hence, there is need to elevate the potential of rain fed agriculture in the midst of the risks posed by climate change. Keywords: Maize Yield, Temperature, Rainfall, Temperature Variability, Rainfall Variability and Climate Change.en_US
dc.language.isoenen_US
dc.publisherMachakos Universityen_US
dc.subjectMaize Yielden_US
dc.subjectClimate Changeen_US
dc.titleClimate Change and Maize Yield in Kenya: An Econometric Analysisen_US
dc.typeLearning Objecten_US


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