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Benefits, costs, and consumer perceptions of the potential introduction of a fungus-resistant banana in Uganda and policy implications

In: Genetically modified crops in Africa: Economic and policy lessons from countries south of the Sahara

  • Kikulwe, Enoch M.
  • Birol, Ekin
  • Wesseler, Justus
  • Falck-Zepeda, Jose Benjamin

Banana is a staple crop in Uganda. Ugandans have the highest per capita consumption of cooking bananas in the world (Clarke 2003). However, banana production in Uganda is limited by several productivity con¬straints, such as insects, diseases, soil depletion, and poor agronomic practices. To address these constraints, the country has invested significant resources in research and development (R&D) and other publicly funded programs, pur¬suing approaches over both the short and long term. Uganda formally initi¬ated its short-term approach in the early 1990s; it involves the collection of both local and foreign germplasms for the evaluation and selection of cultivars tolerant to the productivity constraints. The long-term approach, launched in 1995, includes breeding for resistance to the productivity constraints using conventional breeding methods and genetic engineering. Genetic engineer¬ing projects in Uganda target the most popular and infertile cultivars that can¬not be improved through conventional (cross) breeding.

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This chapter was published in:
  • Falck-Zepeda, Jose Benjamin & Gruère, Guillaume P. & Sithole-Niang, Idah (ed.), 2013. "Genetically modified crops in Africa: Economic and policy lessons from countries south of the Sahara," IFPRI books, International Food Policy Research Institute (IFPRI), number 978-0-89629-795-1.
  • This item is provided by International Food Policy Research Institute (IFPRI) in its series IFPRI book chapters with number 9780896297951-04.
    Handle: RePEc:fpr:ifpric:9780896297951-04
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    1. Rolfe, John & Bennett, Jeff & Louviere, Jordan, 2000. "Choice modelling and its potential application to tropical rainforest preservation," Ecological Economics, Elsevier, vol. 35(2), pages 289-302, November.
    2. Svetlana Edmeades & Melinda Smale, 2006. "A trait-based model of the potential demand for a genetically engineered food crop in a developing economy," Agricultural Economics, International Association of Agricultural Economists, vol. 35(3), pages 351-361, November.
    3. Carlsson, Fredrik & Frykblom, Peter & Liljenstolpe, Carolina, 2003. "Valuing wetland attributes: an application of choice experiments," Ecological Economics, Elsevier, vol. 47(1), pages 95-103, November.
    4. Demont, Matty & Wesseler, Justus & Tollens, Eric, 2003. "Biodiversity versus Transgenic Sugar Beet: The One Euro Question," 2003 Annual Meeting, August 16-22, 2003, Durban, South Africa 25831, International Association of Agricultural Economists.
    5. Eric Ruto & Guy Garrod & Riccardo Scarpa, 2008. "Valuing animal genetic resources: a choice modeling application to indigenous cattle in Kenya," Agricultural Economics, International Association of Agricultural Economists, vol. 38(1), pages 89-98, 01.
    6. Sergio Colombo & Nick Hanley & Jordan Louviere, 2009. "Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 307-322, 05.
    7. Wesseler, Justus & Scatasta, Sara & Nillesen, Eleonora, 2007. "The maximum incremental social tolerable irreversible costs (MISTICs) and other benefits and costs of introducing transgenic maize in the EU-15," MPRA Paper 33229, University Library of Munich, Germany.
    8. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    9. Enoch M. Kikulwe & Ekin Birol & Justus Wesseler & José Falck‐Zepeda, 2011. "A latent class approach to investigating demand for genetically modified banana in Uganda," Agricultural Economics, International Association of Agricultural Economists, vol. 42(5), pages 547-560, 09.
    10. John List & Craig Gallet, 2001. "What Experimental Protocol Influence Disparities Between Actual and Hypothetical Stated Values?," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 20(3), pages 241-254, November.
    11. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74, pages 132.
    12. David Wafula & Norman Clark, 2005. "Science and governance of modern biotechnology in Sub-Saharan Africa-the case of Uganda," Journal of International Development, John Wiley & Sons, Ltd., vol. 17(5), pages 679-694.
    13. Kontoleon Andreas & Yabe Mitsuyasu, 2006. "Market Segmentation Analysis of Preferences for GM Derived Animal Foods in the UK," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 4(1), pages 1-38, December.
    14. List John A. & Sinha Paramita & Taylor Michael H., 2006. "Using Choice Experiments to Value Non-Market Goods and Services: Evidence from Field Experiments," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 5(2), pages 1-39, January.
    15. Peter Boxall & Wiktor Adamowicz, 2002. "Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 23(4), pages 421-446, December.
    16. Guy D. Garrod & Riccardo Scarpa & Kenneth G. Willis, 2002. "Estimating the Benefits of Traffic Calming on Through Routes: A Choice Experiment Approach," Journal of Transport Economics and Policy, London School of Economics and University of Bath, vol. 36(2), pages 211-231, May.
    17. Adam Drucker, 2007. "Measuring Heterogeneous Preferences for Cattle Traits among Cattle-Keeping Households in East Africa," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(4), pages 1005-1019.
    18. Jaffe, Gregory, 2006. "Comparative analysis of the national biosafety regulatory systems in East Africa:," EPTD discussion papers 146, International Food Policy Research Institute (IFPRI).
    19. S. Illeris & G. Akehurst, 2001. "Introduction," The Service Industries Journal, Taylor & Francis Journals, vol. 21(1), pages 1-4, January.
    20. Wuyang Hu, 2004. "Trading off health, environmental and genetic modification attributes in food," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 31(3), pages 389-408, September.
    21. Beckmann, Volker & Soregaroli, Claudio & Wesseler, Justus, 2006. "Governing the Co-existence of GM Crops: Ex-Ante Regulation and Ex-Post Liability under Uncertainty and Irreversibility," Institutional Change in Agriculture and Natural Resources Discussion Papers 18845, Humboldt University Berlin, Department of Agricultural Economics.
    22. Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
    23. Birol, Ekin & Villalba, Eric Rayn & Smale, Melinda, 2007. "Farmer preferences for Milpa diversity and genetically modified maize in Mexico: A latent class approach," IFPRI discussion papers 726, International Food Policy Research Institute (IFPRI).
    24. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    25. Smale, Melinda & Tushemereirwe, Wilbeforce K., 2007. "An economic assessment of banana genetic improvement and innovation in the Lake Victoria Region of Uganda and Tanzania:," Research reports 155, International Food Policy Research Institute (IFPRI).
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