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Ex-Ante Economic Impact Assessment of Genetically Modified Banana Resistant to Xanthomonas Wilt in the Great Lakes Region of Africa.

Ainembabazi JH, Tripathi L, Rusike J, Abdoulaye T, Manyong V - PLoS ONE (2015)

Bottom Line: However, aggregate benefits vary substantially across the target countries ranging from US$ 20 million to 953 million, highest in countries where disease incidence and production losses are high, ranging from 51 to 83% of production.The main beneficiaries of this technology development are farmers and consumers, although the latter benefit more than the former from reduced prices.Designing a participatory breeding program involving farmers and consumers signifies the successful adoption and consumption of GM banana in the target countries.

View Article: PubMed Central - PubMed

Affiliation: International Institute of Tropical Agriculture (IITA), Kampala, Uganda.

ABSTRACT

Background: Credible empirical evidence is scanty on the social implications of genetically modified (GM) crops in Africa, especially on vegetatively propagated crops. Little is known about the future success of introducing GM technologies into staple crops such as bananas, which are widely produced and consumed in the Great Lakes Region of Africa (GLA). GM banana has a potential to control the destructive banana Xanthomonas wilt disease.

Objective: To gain a better understanding of future adoption and consumption of GM banana in the GLA countries which are yet to permit the production of GM crops; specifically, to evaluate the potential economic impacts of GM cultivars resistant to banana Xanthomonas wilt disease.

Data sources: The paper uses data collected from farmers, traders, agricultural extension agents and key informants in the GLA.

Analysis: We analyze the perceptions of the respondents about the adoption and consumption of GM crop. Economic surplus model is used to determine future economic benefits and costs of producing GM banana.

Results: On the release of GM banana for commercialization, the expected initial adoption rate ranges from 21 to 70%, while the ceiling adoption rate is up to 100%. Investment in the development of GM banana is economically viable. However, aggregate benefits vary substantially across the target countries ranging from US$ 20 million to 953 million, highest in countries where disease incidence and production losses are high, ranging from 51 to 83% of production.

Conclusion: The findings support investment in the development of GM banana resistant to Xanthomonas wilt disease. The main beneficiaries of this technology development are farmers and consumers, although the latter benefit more than the former from reduced prices. Designing a participatory breeding program involving farmers and consumers signifies the successful adoption and consumption of GM banana in the target countries.

No MeSH data available.


The upper panel reports the changes in NPV relative to baseline values (Table 6) due to doubling of inputs costs, reduction of initial and ceiling adoption rates by 50%, and reduction of yield by 25%.The middle panel reports the changes in IRR relative to baseline values (Table 6) due to doubling of inputs costs, reduction of initial and ceiling adoption rates by 50%, and reduction of yield by 25%. The bottom panel reports the changes in BCR relative to baseline values (Table 6) due to doubling of inputs costs, reduction of initial and ceiling adoption rates by 50%, and reduction of yield by 25%. Notes: In the upper, the yield gain for Rwanda was reduced by 5% as reduction by 25% would lead to economic losses. In the middle panel, the IRR for Rwanda could not be computed when input costs are doubled, while IRR for Tanzania could not be computed when yield gain was reduced by 25%.
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pone.0138998.g009: The upper panel reports the changes in NPV relative to baseline values (Table 6) due to doubling of inputs costs, reduction of initial and ceiling adoption rates by 50%, and reduction of yield by 25%.The middle panel reports the changes in IRR relative to baseline values (Table 6) due to doubling of inputs costs, reduction of initial and ceiling adoption rates by 50%, and reduction of yield by 25%. The bottom panel reports the changes in BCR relative to baseline values (Table 6) due to doubling of inputs costs, reduction of initial and ceiling adoption rates by 50%, and reduction of yield by 25%. Notes: In the upper, the yield gain for Rwanda was reduced by 5% as reduction by 25% would lead to economic losses. In the middle panel, the IRR for Rwanda could not be computed when input costs are doubled, while IRR for Tanzania could not be computed when yield gain was reduced by 25%.

Mentions: Economic models often have key parameters that drive estimated results. Therefore, it is important to understand the robustness of model results by conducting sensitivity analysis with respect to key parameters. Sensitivity analysis was done to gain some insight about possible future changes in some of the parameters and their potential impact on the estimated economic benefits and costs of adopting GMB-BXW. The baseline results reported (Table 6) proved robust to some changes in the assumed levels of analyzed parameters reported in Fig 9. The projected increase in input costs because of adopting GMB-BXW was fairly low at 32% on average, while the initial and ceiling adoption rates were as high as up to 70% and 100%, respectively (Table 4). The expected yield gain after the adoption of GMB-BXW was also fairly high but with marked variability across countries, ranging from 25–70%. Holding the discount rate fixed at 10%, we doubled the total input costs, reduced the initial and ceiling adoption rates by 50%, and reduced the maximum yield gain by 25%, and then recalculated NPV, IRR and BCR. However, by reducing the maximum yield gain by 25% in Rwanda would lead to economic losses. We therefore reduced the maximum yield gain by 5% for this country. Also note that this reduction in yield gain (by 5% in Rwanda and 25% in Tanzania) could not allow computation of IRR for these countries. A similar problem was encountered in case of doubling costs for Rwanda. The upper panel of Fig 9 shows that changes in input costs or adoption rates have no significant impacts on NPV, suggesting that adoption of GMB-BXW remains economically viable despite increases in input costs or reductions in adoption rates. However, a reduction of 25% in the expected yield gain considerably reduces NPV, suggesting that yield improvement represents one of key factors affecting changes in net benefits and so is the potential likelihood of adopting GMB-BXW.


Ex-Ante Economic Impact Assessment of Genetically Modified Banana Resistant to Xanthomonas Wilt in the Great Lakes Region of Africa.

Ainembabazi JH, Tripathi L, Rusike J, Abdoulaye T, Manyong V - PLoS ONE (2015)

The upper panel reports the changes in NPV relative to baseline values (Table 6) due to doubling of inputs costs, reduction of initial and ceiling adoption rates by 50%, and reduction of yield by 25%.The middle panel reports the changes in IRR relative to baseline values (Table 6) due to doubling of inputs costs, reduction of initial and ceiling adoption rates by 50%, and reduction of yield by 25%. The bottom panel reports the changes in BCR relative to baseline values (Table 6) due to doubling of inputs costs, reduction of initial and ceiling adoption rates by 50%, and reduction of yield by 25%. Notes: In the upper, the yield gain for Rwanda was reduced by 5% as reduction by 25% would lead to economic losses. In the middle panel, the IRR for Rwanda could not be computed when input costs are doubled, while IRR for Tanzania could not be computed when yield gain was reduced by 25%.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4587572&req=5

pone.0138998.g009: The upper panel reports the changes in NPV relative to baseline values (Table 6) due to doubling of inputs costs, reduction of initial and ceiling adoption rates by 50%, and reduction of yield by 25%.The middle panel reports the changes in IRR relative to baseline values (Table 6) due to doubling of inputs costs, reduction of initial and ceiling adoption rates by 50%, and reduction of yield by 25%. The bottom panel reports the changes in BCR relative to baseline values (Table 6) due to doubling of inputs costs, reduction of initial and ceiling adoption rates by 50%, and reduction of yield by 25%. Notes: In the upper, the yield gain for Rwanda was reduced by 5% as reduction by 25% would lead to economic losses. In the middle panel, the IRR for Rwanda could not be computed when input costs are doubled, while IRR for Tanzania could not be computed when yield gain was reduced by 25%.
Mentions: Economic models often have key parameters that drive estimated results. Therefore, it is important to understand the robustness of model results by conducting sensitivity analysis with respect to key parameters. Sensitivity analysis was done to gain some insight about possible future changes in some of the parameters and their potential impact on the estimated economic benefits and costs of adopting GMB-BXW. The baseline results reported (Table 6) proved robust to some changes in the assumed levels of analyzed parameters reported in Fig 9. The projected increase in input costs because of adopting GMB-BXW was fairly low at 32% on average, while the initial and ceiling adoption rates were as high as up to 70% and 100%, respectively (Table 4). The expected yield gain after the adoption of GMB-BXW was also fairly high but with marked variability across countries, ranging from 25–70%. Holding the discount rate fixed at 10%, we doubled the total input costs, reduced the initial and ceiling adoption rates by 50%, and reduced the maximum yield gain by 25%, and then recalculated NPV, IRR and BCR. However, by reducing the maximum yield gain by 25% in Rwanda would lead to economic losses. We therefore reduced the maximum yield gain by 5% for this country. Also note that this reduction in yield gain (by 5% in Rwanda and 25% in Tanzania) could not allow computation of IRR for these countries. A similar problem was encountered in case of doubling costs for Rwanda. The upper panel of Fig 9 shows that changes in input costs or adoption rates have no significant impacts on NPV, suggesting that adoption of GMB-BXW remains economically viable despite increases in input costs or reductions in adoption rates. However, a reduction of 25% in the expected yield gain considerably reduces NPV, suggesting that yield improvement represents one of key factors affecting changes in net benefits and so is the potential likelihood of adopting GMB-BXW.

Bottom Line: However, aggregate benefits vary substantially across the target countries ranging from US$ 20 million to 953 million, highest in countries where disease incidence and production losses are high, ranging from 51 to 83% of production.The main beneficiaries of this technology development are farmers and consumers, although the latter benefit more than the former from reduced prices.Designing a participatory breeding program involving farmers and consumers signifies the successful adoption and consumption of GM banana in the target countries.

View Article: PubMed Central - PubMed

Affiliation: International Institute of Tropical Agriculture (IITA), Kampala, Uganda.

ABSTRACT

Background: Credible empirical evidence is scanty on the social implications of genetically modified (GM) crops in Africa, especially on vegetatively propagated crops. Little is known about the future success of introducing GM technologies into staple crops such as bananas, which are widely produced and consumed in the Great Lakes Region of Africa (GLA). GM banana has a potential to control the destructive banana Xanthomonas wilt disease.

Objective: To gain a better understanding of future adoption and consumption of GM banana in the GLA countries which are yet to permit the production of GM crops; specifically, to evaluate the potential economic impacts of GM cultivars resistant to banana Xanthomonas wilt disease.

Data sources: The paper uses data collected from farmers, traders, agricultural extension agents and key informants in the GLA.

Analysis: We analyze the perceptions of the respondents about the adoption and consumption of GM crop. Economic surplus model is used to determine future economic benefits and costs of producing GM banana.

Results: On the release of GM banana for commercialization, the expected initial adoption rate ranges from 21 to 70%, while the ceiling adoption rate is up to 100%. Investment in the development of GM banana is economically viable. However, aggregate benefits vary substantially across the target countries ranging from US$ 20 million to 953 million, highest in countries where disease incidence and production losses are high, ranging from 51 to 83% of production.

Conclusion: The findings support investment in the development of GM banana resistant to Xanthomonas wilt disease. The main beneficiaries of this technology development are farmers and consumers, although the latter benefit more than the former from reduced prices. Designing a participatory breeding program involving farmers and consumers signifies the successful adoption and consumption of GM banana in the target countries.

No MeSH data available.