Adoption of GM crops in Ghana: Ex ante estimations for insect-resistant cowpea and nitrogen-use efficient rice - Dzanku, Fred M.; Zambrano, Patricia; Wood-Sichra, Ulrike; Falck-Zepeda, José B.; Chambers, Judith A.; Hanson, Hillary; Boadu, Paul; Science and Technology Policy Research Institute (International Food Policy Research Institute, 2018)
This paper uses an innovative research process to quantify the potential impacts of releasing and adopting insect-resistant (IR) cowpea and nitrogen-use efficient (NUE) rice in Ghana using an economic surplus partial equilibrium model. The premise of the research process was to build national capacity to produce timely and robust estimates, based on secondary data and qualified experts’ informed opinions, collected in country. Ghana’s stakeholders selected the two genetically modified (GM) technologies discussed here based on their assessment of these GM products’ regulatory advancement and their economic and political importance. Using assumptions regarding the expected changes from the adoption and commercialization of these crops, collected from national and international crop and technology experts, the authors estimate that the benefits of adopting IR cowpea are between US$5.5 million and US$125.3 million, and between US$1.9 million and US$153 million for NUE rice. The analysis also shows how a five-year regulatory delay may erode these benefits, reducing them by between 29 and 39 percent for IR cowpea and between 28 and 57 percent for NUE rice. Additionally, the authors make preliminary estimates of sex-disaggregated benefits and calculate the unequal distribution of benefits between female and male producers and consumers owing to gender disparities in production and consumption. The welfare estimations are based on an economic surplus model that were estimated using the DREAM software. Although this partial equilibrium model has limitations regarding market-clearing assumptions and is specific to a product, it is a data-parsimonious method that can produce results in a short time frame, which might better suit policymakers’ and decision makers’ demands for rapid estimations.