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Assessment Of The Socioeconomic Effects Of The Napier Stunt Disease On Small Scale Dairy Production In Bungoma District, Kenya

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  • Amiani, Lydia Vihenda

Abstract

Napier grass stunt disease (NSD) has been a major challenge to sustainable smallholder dairy production in Kenya. A household (HH) survey was conducted using personal interviews to assess the effect of NSD on level of milk production and on milk income at household level in Bungoma District, Western Kenya. Data were collected using structured questionnaires in a cross-sectional survey involving 130 respondents in five selected divisions of the larger Bungoma District. Descriptive statistics were used to assess farmers‟ opinions on the extent of NSD infestation on farms. Cobb Douglas (CD) two stage least square (2SLS) model was used to determine the effects of NSD and other variables on the yield of milk. A log linear regression was used to determine the effects of NSD and other variables on the household milk income. Descriptive results indicate that there was an average drop from two cows to one cow that could be fed on an acre of Napier. The CD 2SLS results show that the area under Napier had a positive significant effect on the area of Napier grass under the NSD. Furthermore, NSD had a significant negative impact on milk yield (p<0.05). Gender, farming experience, and alternative sources of feed were found to have a significant negative influence on milk yield. Prevailing market milk price and number of cattle had a positive influence on milk yield. Napier stunt disease had a significant negative impact on monthly gross margins (GM) per cow (p<0.05). The estimates in Kshs were 4325, 4122, 1433, 2689 and 1782 for Kibabii, Sang‟alo, Bumula, Malakisi and Webuye, respectively. The GM estimates were also influenced by other household characteristics such as HH size, push pull practice, land under Napier grass, milk output, and milk prices all of which had a positive impact. The study provides useful information about the effects of the NSD on small scale dairy production and on specific socioeconomic parameters that farmers, extensionists, researchers and policy makers can use in designing appropriate interventions towards mitigating the negative effects of NSD on overall dairy productivity.

Suggested Citation

  • Amiani, Lydia Vihenda, 2011. "Assessment Of The Socioeconomic Effects Of The Napier Stunt Disease On Small Scale Dairy Production In Bungoma District, Kenya," Research Theses 157510, Collaborative Masters Program in Agricultural and Applied Economics.
    • Handle: RePEc:ags:cmpart:157510
    DOI: 10.22004/ag.econ.157510
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    1. Harold J. Brumm and Dale O. Cloninger, 1995. "The Drug War and the Homicide Rate: A Direct Correlation?," Cato Journal, Cato Journal, Cato Institute, vol. 14(3), pages 509-517, Winter.
    2. Keeney,Ralph L. & Raiffa,Howard, 1993. "Decisions with Multiple Objectives," Cambridge Books, Cambridge University Press, number 9780521438834, November.
    3. Richard E. Just & David Zilberman & Eithan Hochman, 1983. "Estimation of Multicrop Production Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 65(4), pages 770-780.
    4. Walshe, M.J. & Grindle, J. & Nell, A. & Bachmann, M., 1991. "Dairy development in Sub-Sahara Africa: A study of issues and options," Papers 135, World Bank - Technical Papers.
    5. V. M. Manyong & I. Okike & T. O. Williams, 2006. "Effective dimensionality and factors affecting crop‐livestock integration in West African savannas: a combination of principal component analysis and Tobit approaches," Agricultural Economics, International Association of Agricultural Economists, vol. 35(2), pages 145-155, September.
    6. Kuchler, Fred & Duffy, Michael & Shrum, R. D. & Dowler, W. M., 1984. "Potential Economic Consequences of the Entry of an Exotic Fungal Pest: The Case of Soybean Rust," Staff General Research Papers Archive 11056, Iowa State University, Department of Economics.
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