Consumer willingness to pay for genetically modified food in Kenya

Genetically modified (GM) crops are popular in many regions of the world, but their deployment in Africa is hindered by safety concerns and regulatory issues, although the continent is in dire need of boosting its food production. Although consumers' acceptance of GM food has been analyzed in many continents, no such studies have been conducted in Africa. Therefore, a survey of 604 consumers was conducted in Nairobi, Kenya, in 2003, to gauge consumers' awareness of GM crops, their willingness to pay (WTP) for GM food, and the factors that influence their WTP. Consumers' knowledge of GM crops was limited and only 38% of the 604 respondents were aware of GM crops. People in higher education and income groups were more aware than others. Regardless, people were generally appreciative of the technology, and a large majority (68%) would be willing to buy GM maize meal at the same price as their favorite brand. Consumers were, however, concerned about possible side effects, especially on the environment and biodiversity. WTP was estimated using a double‐bounded dichotomous choice model, and the mean WTP was found to be 13.8% higher than the average price of non‐GM maize meal. Perceptions of health risk, and ethical and equity concerns had a negative influence on the likelihood of purchasing GM maize meal, whereas trust in government to ensure food quality had a positive influence on WTP. People with at least some secondary education and those in the high‐income category were more likely to purchase GM maize meal at the same price. The study concludes that, because awareness is still low, appropriate communications are needed to involve the consumer in the debate. Consumers' acceptance in this study was high, but the research needs to be expanded to rural areas, where most consumers live, and other survey methods need to be explored.     

A trait-based model of the potential demand for a genetically engineered food crop in a developing economy

We predict the potential demand of smallholder farmers for genetically transformed varieties of a food crop, the cooking banana of the East African highlands. Farmer demand for planting material is derived in an agricultural household model that accounts for variety traits and missing markets. The demand for candidate host varieties is predicted using a Zero‐Inflated Poisson (ZIP) regression system. The fitted model is used to illustrate the sensitivity of farmer demand for improved planting material to (a) investments in research and development, represented by the effectiveness of gene insertion and expression, and (b) other public investments in education, extension, and market infrastructure that support diffusion. By comparing the characteristics of agricultural households we demonstrate that the choice of host variety can have social consequences, favoring one rural population compared with another. Clients for transgenic banana planting material are likely to be poorer, subsistence‐oriented farmers in areas greatly affected by biotic constraints. A model of this type might be useful in assessing the investments needed to support the systematic dissemination of improved planting material. The approach can be generalized to other crop biotechnologies for smallholder farming systems, particularly in developing economies.     

Diffusion and spillover of new technology: a heterogeneous-agent model for cassava in West Africa

Understanding what determines the geographic spread of innovations can help guide the funding and implementation of research and extension programs. Our approach uses household survey data as model parameters, to simulate behavior across the entire surveyed population and avoid the aggregation bias associated with representative‐farm models. Such a “heterogeneous agent” approach allows us to infer the distribution of a technology's impacts across one set of households, and predict the potential for spreading to another set that shares similar characteristics with respect to natural resource endowments and farming systems. We apply the technique to new cassava varieties in West Africa, finding a strongly poverty‐alleviating impact, with substantial spillover potential from Nigeria to neighboring countries.     

Market imperfections,access to information and technology adoption in Uganda: challenges of overcoming multiple constraints

Limited empirical evidence exists on how multiple binding constraints influence the adoption of improved technologies by smallholder farmers. This article uses the case of groundnut variety adoption in Uganda to investigate the role of information, seed supply, and credit constraints in conditioning technology uptake. New data from a household survey in seven groundnut growing districts (n = 945) indicate that 8% of farmers lack information on new varieties, while 18% and 6% of farmers, respectively, cannot adopt mainly due to seed supply and capital constraints. A tobit‐type specification that considers all nonadopters as being uninterested in the technology (i.e., corner solutions) would lead to inconsistent parameter estimates and incorrect conclusions in this context. We therefore estimate a modified multi‐hurdle specification of demand for new varieties, taking into account how information, seed supply, and capital constraints jointly determine adoption probability and intensity. The study reveals new empirical insights on why agricultural technology adoption in Africa has lagged behind: slow uptake is not mainly due to a lack of economic incentives, but rather a reflection of information, seed supply, and credit constraints that prevent farmers from translating their desired demand into adoption of modern varieties. Policy implications are discussed.     

The use of latent classes to identify individual differences in the importance of landscape dimensions for aesthetic preference

Most literature in landscape perception and preference has focused on aesthetic preference by (groups of) people. Factors that could influence the aesthetic preference, such as landscape dimensions and observer's background characteristics, are far less examined. This may be due to the increasing complexity of the dataset, when variation both in landscape attributes and respondents’ characteristics is to be included in the models. The complex multivariate analysis models that emerge require more sophisticated statistical analysis. Also, the conclusions that result from the traditional analysis sound like, e.g. experts show lower preferences than nonexperts, which is rather deterministic and leaves no room for fuzziness. Latent class analysis provides an opportunity to include fuzziness, by only probabilistically assigning respondents in a latent class in function of the respondent's characteristics. The present paper explores the use of latent class analysis to determine individual differences in the importance appended to several landscape dimensions for landscape aesthetic preference. A questionnaire survey was executed in a spatially stratified sample amongst inhabitants of the city of Ghent (Flanders, Belgium). Latent preference classes are identified of which the cases vary in the level of importance attached to landscape characteristics for aesthetic preference. Care and disturbance appear to have larger effect on preference than naturalness and urbanisation. The effect of care and disturbance on landscape aesthetic preference also most significantly distinguishes between the latent preference classes. The importance of openness for aesthetics is small and not significantly dependent on the individual background of the observer. Respondents’ characteristics that affect the probability of belonging to a latent preference class are environmental behaviour and attitude, actual living environment, age class, education level, and organisation membership. Understanding the basis for differences in landscape preference may respond to tastes and aspirations of the general public, putting landscape planning in the broader context of society.     

Demand for a labor‐based drought insurance scheme in Ethiopia: a stated choice experiment approach

Index‐based weather insurance is increasingly used to manage weather‐related risks in smallholder agriculture. However, cash‐constrained smallholders often lack the resources to pay an insurance premium, which may undermine its wider adoption. This article investigates alternative insurance payment methods that may help to enhance the adoption of index‐based weather insurance. We use a choice experiment to elicit smallholders’ willingness to pay in cash or labor for index‐based weather insurance in four districts in the south‐central highlands of Ethiopia. The insurance schemes were created using a fractional factorial design with three factors: work, cash, and payout rate. We analyze the choice data using a random parameter mixed logit model. We find that the average participants need a subsidy to pay cash for insurance because their willingness to pay is less than the expected cost of the insurance. On average, they are willing to pay only 0.81 ETB (Ethiopian currency) to get an expected yearly payout of 1 ETB. However, most are willing to participate in work‐for‐insurance programs at lower daily wage rates than is common for other work programs in Ethiopia.     

International research on vegetable improvement in East and Southern Africa: adoption,impact, and returns

There is a lack of evidence for impact at scale of vegetable research and development, although the importance of vegetables for human nutrition and smallholder incomes is generally understood. We therefore study adoption and impact of improved tomato and African eggplant varieties developed through international agricultural research, released by national agricultural research and extension systems, and supplied to farmers by private seed companies in East and Southern Africa from 1990 to 2014. The study finds that in 2014, varieties developed by the World Vegetable Center accounted for 50% of tomato and 98% of African eggplant commercial seed production in East and Southern Africa. For Tanzania alone, investment in crop improvement generated economic gains of US$ 255 million for tomato and US$ 5 million for African eggplant up to 2014. The internal rate of return is 26% for tomato and 12% for African eggplant, though we project the latter to increase to 26% by 2024 as the variety was released only in 2007. These findings support the view that agricultural policy and investment reoriented towards contemporary nutritional challenges will give high returns to investment.     

Yield Effects of Tissue Culture Bananas in Kenya: Accounting for Selection Bias and the Role of Complementary Inputs

We analyse yield effects of tissue culture (TC) banana technology in the Kenyan small farm sector, using recent survey data and an endogenous switching regression approach. TC banana plantlets, which are free from pests and diseases, have been introduced in East Africa since the late 1990s. Although field experiments show significant yield advantages over traditional banana suckers, a rigorous assessment of impacts in farmers’ fields is still outstanding. A comparison of mean yield levels between TC adopters and non‐adopters in our sample shows no significant difference. However, we find evidence of negative selection bias, indicating that farmers with lower than average yields are more likely to adopt TC. Controlling for this bias results in a positive and significant TC net yield gain of 7%. We also find that TC technology is more knowledge intensive and more responsive to irrigation than traditional bananas. Simulations show that improving access to irrigation could lift TC productivity gains to above 20%. The analytical approach developed and applied here and the finding of negative selection bias may also be relevant for the evaluation of other agricultural technologies.     

Gender and agriculture in sub‐Saharan Africa: introduction to the special issue

This special issue contributes to the literature on gender differences in sub‐Saharan African agriculture primarily by using new and innovative micro‐data. The first six articles have a strong focus on understanding the extent and drivers of gender differences in land productivity and use data from nationally representative household surveys that are implemented under the Living Standards Measurement Study‐Integrated Surveys on Agriculture (LSMS‐ISA) initiative. The LSMS‐ISA data are multi‐topic, with geo‐referenced household and plot locations, and information on production and identity of managers and owners at the plot level. The last two articles in the volume rely on in‐depth quantitative and qualitative case study data, which, in combination with the nationally representative data, allow for greater insights into the extent and correlates of gender differences in sub‐Saharan African agriculture. While there does seem to be persistent evidence of gender gaps, the studies find the sources of these gaps to vary within and across countries. This makes designing policies to address gender gaps more challenging, yet of crucial importance. What is clear is that the failure to directly and explicitly address the underlying causes of the disparities is likely to end up exacerbating the observed gender gaps.     

Ex Ante Impact Assessment under Imperfect Information: Biotechnology in New Member States of the EU

Some argue that the lack of modern agricultural development in the former socialist countries of Central and Eastern Europe has made cutting‐edge biotechnology attractive. However, enthusiasm for planting genetically modified (GM) crops varies greatly in the enlarged European Union (EU) and especially among the New Member States (NMS); the Czech GM maize area is progressively growing whereas Hungary imposed a de facto ban on GM crops. Remarkably, the Hungarian ban was not supported by any cost–benefit assessment. In the literature, ex ante impact assessments of monopolistically priced technologies are often based on cross‐sectional comparisons of average cropping budgets. Such assessments ignore heterogeneity of farmers and underestimate the true impact of these technologies because of homogeneity bias. Therefore, we propose an improved method by explicitly modelling farmer heterogeneity under imperfect information, and assess the potential value and benefit sharing of GM crops in the two NMS using a stochastic partial equilibrium model. The total potential value of GM crops is estimated at €82 million for both countries, of which €60 million (73%) accrues to farmers and €22 million (27%) to the gene developers and the seed industry. This is in line with the literature on global benefit sharing of first‐generation GM technologies.     

Consumer Acceptance of Second‐Generation GM Foods: The Case of Biofortified Cassava in the North‐east of Brazil

Biofortified staple foods are currently being developed to reduce problems of micronutrient malnutrition among the poor. This partly involves use of genetic modification. Yet, relatively little is known about consumer acceptance of such second‐generation genetically modified (GM) foods in developing countries. Here, we analyse consumer attitudes towards provitamin A GM cassava in the north‐east of Brazil. Based on stated preference data, mean willingness to pay is estimated at 60–70% above market prices for traditional cassava. This is higher than the results from similar studies in developed countries, which is plausible given that micronutrient malnutrition is more severe in developing countries. GM foods with enhanced nutritive attributes seem to be well received by poor consumers. However, the results also suggest that acceptance would be still higher if provitamin A were introduced to cassava through conventional breeding. Some policy implications are discussed.