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dc.contributor.authorMuricho, GS
dc.date.accessioned2013-03-15T12:57:24Z
dc.date.issued2002
dc.identifier.citationMsc - Thesisen
dc.identifier.urihttp://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/14167
dc.descriptionMsc - Thesisen
dc.description.abstractThis study aimed at identifying and analyzing the performance of the major marketing channels of dry grain pigeonpea in Kenya. Makueni District was used as a case study. As such, the various marketing intermediaries in this sub-sector were identified together with the different technologies they use to perform their marketing functions. Three main channels in this sub-sector were identified i.e. farm gate to urban open air retail of the grain, farm gate to retail of the grain in urban supermarkets and farm gate to export of the grain. At the same time, the six major marketing intermediaries identified were; rural assemblers, rural wholesalers, urban wholesalers, urban open-air retailers, urban supermarket retailers and urban whole grain exporters. The costs incurred (cost of the grain, transport, storage, grain cleaning, chemicals and empty bags) and revenue earned at each level in each marketing channel was ascertained. Particularly important in this study was the consideration of transaction costs as they occur at each level in each marketing channel. The transaction costs considered herein were those costs associated with buying or selling of poor quality grain (adverse selection) and the opportunity cost of time associated with assembling of small units of the grain from the various producing farmers scattered all over the rural places. There are many other transaction costs in this sub-sector but the current study narrowed down to these two due to their implications on the farmers‟ price and quality competitiveness. xi Thereafter, a Policy Analysis Matrix (PAM) framework that was developed by Monke and Pearson (1989) was used as a tool to analyze the performance of the identified channels so as to test the two hypotheses of the study i.e. that dry grain pigeonpea marketing channels are competitive and that transaction costs affect the competitiveness of the dry grain pigeonpea marketing channels significantly. This was achieved by construction of three main PAM ratios from the PAM entries. These were Private Cost Ratio (PCR), Domestic Resource Cost ratio (DRC) and Nominal Protection Coefficient (NPC). The results showed that transaction costs are more significant at the post farm level in this sub-sector than farm level. Generally, post farm marketing activities were found to be more competitive both privately and socially as they had the lowest PCR and DRC ratios respectively. Before accounting for the estimated transaction costs, the PCR at farm level was 0.7 while channels 1, 2, and 3 had PCR of 0.25, 0.26 and 0.19 respectively. On the other hand, DRC at farm level was 0.37 while channels 1, 2, and 3 had DRC of 0.32, 0.40, and 0.26 respectively. It was also evident from the NPC that farm level output prices are well below their world market equivalent i.e. farm level NPC was 0.55 whereas post farm prices are well above their world market equivalent i.e. channels 1, 2, and 3 had NPC of 1.18, 1.38, and 1.21 respectively. Conclusively, an alternative marketing arrangement of integrating the whole grain export market was recommended to improve the farmers‟ price competitiveness. Thus the export market was the recommended channel of the study if this crop is to be fully commercialized given the fact that most xii producers of this crop prefer consuming it as green vegetable rather than dry grain because it takes a long time to cook and they also belief that eating a lot of dry grain pigeonpea causes madness.en
dc.description.sponsorshipUniversity of Nairobien
dc.language.isoenen
dc.subjectImpacten
dc.subjectTransaction Costsen
dc.subjectMarketing channelsen
dc.subjectDry Grain pigeonpeaen
dc.subjectMakuenien
dc.subjectKenyaen
dc.titleImpact of transaction costs on the marketing channels of dry grain pigeonpea in Makueni district, Kenya.en
dc.typeThesisen
local.publisherDepartment of Agricultural Economics, University of Nairobi, Kenyaen


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