SummaryThis report presents the results <strong>of</strong> the basel<strong>in</strong>e study undertaken to assess the status <strong>of</strong> <strong>Striga</strong>damage, the general livelihoods and livelihood strategies <strong>of</strong> the rural poor <strong>in</strong> western <strong>Kenya</strong>.A stratified random sampl<strong>in</strong>g method led to the selection <strong>of</strong> 8 districts, 16 sub-locations, 32villages and 800 households. A comb<strong>in</strong>ation <strong>of</strong> techniques for data collection was used,<strong>in</strong>clud<strong>in</strong>g literature review, GPS record<strong>in</strong>gs, focus group discussions and <strong>in</strong>terview <strong>of</strong><strong>in</strong>dividual households. Various econometric models were also developed and estimated fordata analyses. A stochastic frontier production function was used to measure the technicalefficiency <strong>of</strong> maize production. A logistic regression model <strong>of</strong> poverty was estimated toexam<strong>in</strong>e the determ<strong>in</strong>ants and correlates <strong>of</strong> poverty <strong>in</strong> western <strong>Kenya</strong>.The study revealed that households are small <strong>in</strong> size and the dependency ratio is high. Therewere about 26% <strong>of</strong> households headed by females. The level <strong>of</strong> education is low for the heads<strong>of</strong> households and all members <strong>of</strong> farm families. Households are endowed with a multitude <strong>of</strong>assets for their livelihoods. However, the level <strong>of</strong> assets was found to be low or <strong>of</strong> very poorquality. <strong>Maize</strong> is the major food crop and a source <strong>of</strong> cash <strong>in</strong>come. Farmers grow both localand improved (hybrid) maize varieties, but the productivity is low. There is a considerablegap between potential and actual maize yields. Major factors constra<strong>in</strong><strong>in</strong>g crop production<strong>in</strong>clude <strong>Striga</strong> <strong>in</strong>festation on maize, low soil fertility, drought and erratic ra<strong>in</strong>fall. <strong>Striga</strong> is themajor threat to livelihoods <strong>of</strong> smallholders and its economic importance has <strong>in</strong>creased overthe past three decades. Traditional methods <strong>of</strong> <strong>Striga</strong> control <strong>in</strong>clude uproot<strong>in</strong>g, burn<strong>in</strong>g andmanur<strong>in</strong>g, which have proved to be <strong>in</strong>effective. Alternative technologies exist but they havenot been adopted and used as they should because the level <strong>of</strong> awareness is very low.Analysis <strong>of</strong> the determ<strong>in</strong>ants <strong>of</strong> poverty revealed that the poverty status <strong>of</strong> a household <strong>in</strong>western <strong>Kenya</strong> is significantly related to <strong>Striga</strong> damage, <strong>Striga</strong> control, dependency ratio,age, education, technology adoption, land per capita, farm assets, <strong>of</strong>f-farm work, cash cropproduction, and location.More than 70% <strong>of</strong> the sampled households experience food shortage last<strong>in</strong>g as long as fivemonths every year. Cop<strong>in</strong>g strategies <strong>in</strong>clude <strong>of</strong>f-farm short-term jobs, disposal <strong>of</strong> assets, and<strong>in</strong>formal safety nets especially through remittances received from relatives. Theanthropometric Z scores calculated on children <strong>in</strong>dicate that about 30% were wast<strong>in</strong>g, 50%were underweight and 48% were stunted. Similarly, the results on body mass <strong>in</strong>dex (BMI) onwomen showed that 36% were underweight while 18% were overweight.One <strong>of</strong> the possible strategies to reduce poverty and vulnerability is to <strong>in</strong>crease the efficiency<strong>in</strong> maize production. Considerable variation <strong>in</strong> maize production efficiency was found amongthe sample maize farmers. The results po<strong>in</strong>t to the possibility <strong>of</strong> <strong>in</strong>creas<strong>in</strong>g maize productionthrough improved efficiency and best local practices adopted by the most efficient farmers <strong>in</strong>the sample, such as <strong>in</strong>tegrated <strong>Striga</strong> control. While technical efficiency <strong>in</strong>creases witheducational atta<strong>in</strong>ment, it has a significant non-l<strong>in</strong>ear relationship with farm size where it first<strong>in</strong>creases but eventually decl<strong>in</strong>es with farm size. The direct farm size-efficiency relationshipfor smaller hold<strong>in</strong>gs coupled with the fact that most farmers <strong>in</strong> western <strong>Kenya</strong> cultivate t<strong>in</strong>yplots <strong>of</strong> land suggests that re-allocation <strong>of</strong> more land to maize would enhance farmerefficiency. Increased efficiency could be achieved through, for <strong>in</strong>stance, more optimalapplication <strong>of</strong> <strong>in</strong>puts and greater <strong>in</strong>tensity <strong>of</strong> adoption <strong>of</strong> improved maize varieties. Therefore,efforts must be made to enhance adoption <strong>of</strong> both hybrid maize and <strong>Striga</strong> controltechnologies to help <strong>in</strong>crease maize production. <strong>Maize</strong> yields <strong>in</strong> <strong>Kenya</strong> have cont<strong>in</strong>ued todecl<strong>in</strong>e despite <strong>in</strong>creased use <strong>of</strong> new maize varieties, largely due to lack <strong>of</strong> effective <strong>Striga</strong>6
control technologies. Promot<strong>in</strong>g both high-yield<strong>in</strong>g varieties and <strong>Striga</strong> control technologiesshould thus be an important goal for research and extension <strong>in</strong> <strong>Kenya</strong>.7
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