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.     

Soil quality and fertilizer use rates among smallholder farmers in western Kenya

Studies of fertilizer use in sub-Saharan Africa have been dominated by analyses of economic and market factors having to do with infrastructure, institutions, and incentives that prevent or foster increased fertilizer demand, largely ignoring how soil fertility status conditions farmer demand for fertilizer. We apply a switching regression model to data from 260 farm households in western Kenya in order to allow for the possibility of discontinuities in fertilizer demand based on a soil carbon content (SCC) threshold. We find that the usual factors reflecting liquidity and quasi-fixed inputs are important on high-SCC plots but not on those with poorer soils. External inputs become less effective on soils with low SCC, hence the discernible shift in behaviors across soil quality regimes. For many farmers, improved fertilizer market conditions alone may be insufficient to stimulate increased fertilizer use without complementary improvements in the biophysical conditions that affect conditional factor demand.     

The effects of a large discrete maize price increase on the distribution of household welfare and poverty in rural Kenya1

This study estimates the effects of a large discrete maize price increase on the welfare of a sample of rural Kenyan households. The usual first‐order welfare approximation formula is extended to a second‐order formula that allows for supply and demand responses to the price change. Results show that many rural households are not affected greatly by the price change, and there are about as many gainers as losers. However, these full sample results mask important differences across regions. Welfare gains generally take place in major production areas while losses are in areas where most households are net buyers of maize. Semiparametric methods are used to investigate the relationship between income and the size of the welfare effect, and poverty dominance techniques are applied to study the impacts of the maize price increase on rural poverty.     

Agricultural technology adoption and child nutrition enhancement: improved maize varieties in rural Ethiopia

Adoption of improved crop varieties can lead to multiple benefits to farm households, including increased productivity, incomes, and food consumption. However, possible impacts of adoption on child nutrition outcomes are rarely explored in the literature. This article helps bridge this gap through an impact assessment of the adoption of improved maize varieties (IMVs) on child nutrition outcomes using a recent household survey from rural Ethiopia. The conceptual linkage between IMV adoption and child nutrition is first established using an agricultural household model. Instrumental variable estimation suggests the overall impacts of adoption on child height‐for‐age and weight‐for‐age z‐scores to be positive and significant. Quantile instrumental variable regressions further reveal that such impacts are largest among children with poorest nutrition outcomes. Finally, by combining a decomposition procedure with system of equations estimation, it is found that the increase in own‐produced maize consumption is the major channel through which IMV adoption affects child nutrition.     

Improving the speed of adoption of agricultural technologies and farm performance through farmer groups: evidence from the Great Lakes region of Africa

The article examines the effect of membership in farmer groups (MFG) on adoption lag of agricultural technologies and farm performance in Burundi, the Democratic Republic of Congo and Rwanda. We use duration and stochastic production frontier models on farm household data. We find that the longer the duration of MFG, the shorter the adoption lag and much more so if combined with extension service delivery. Farmer groups function as an important mechanism for improving farm productivity through reduced technical inefficiency in input use. We discuss policy implications under which farmer groups are a useful channel to reduce adoption lag, and the means through which improved farm performance can be achieved.     

The impact of water conservation and intensification technologies: empirical evidence for rice farmers in Ghana

This study employs the propensity score matching model to examine the impact of the adoption of water conservation and intensification technologies on farm output and income among small-scale lowland rice farmers in the Northern Region of Ghana. The matching was conducted based on the Mahalanobis distance combined with the propensity score. Balancing tests by checking the mean standardized absolute bias in the matched sample were conducted as well as a sensitivity analysis was conducted to check for hidden bias due to unobservable selection. The empirical results show a positive and significant impact of the adoption of bunds technology on input demand as well as a positive but insignificant impact on output supply and net returns. Adopters of the dibbling technology were found to have higher output supply, whereas no statistically significant difference was found between the incomes of adopters and nonadopters of dibbling seed method. The results, however, reveal a positive and significant effect on output and net returns when the dibbling method is combined with intensified weeding. The estimates were found to be relatively insensitive to hidden bias.     

Demand for improved fish feed in the presence of a subsidy: a double hurdle application in Kenya

Fish farming households’ demand for improved fish feed from the private market in Kenya is potentially influenced by the government's feed subsidy program. This article applies the double‐hurdle model to a cross‐section of fish farms to analyze demand for improved fish feed from private markets, and whether the government feed subsidy program has an effect on private demand for improved feed. The results indicate that households’ decisions to participate in the improved feed market are affected by the quantity of improved feed received from the government. Once the participation decision has been made, we find evidence of crowding‐in of the private improved feed sector; that is, the government's allocations of subsidized feed appear to increase private sector demand. In addition, the price of improved feed negatively affects the quantity purchased as expected. Education, extension contacts, and ease of marketing matured fish increase household propensity to purchase improved feed commercially. Policies that help reduce the price of improved feed such as reduction in tariffs on imported feeds and feed ingredients will foster demand for the feed, as will policies that facilitate marketing of fish at reasonable prices by households.     

Demand for temperature and rainfall index insurance in India

Weather index insurance has been attracting considerable attention from academics and policymakers. This study investigates the demand for two types of index insurance sold in India: temperature index insurance for dry season and rainfall index insurance for subsequent monsoon season. Using data from randomized subsidy experiments, we separate purchase and quantity decisions and investigate how demand for rainfall insurance is correlated with demand for temperature insurance sold in the previous season. We find that the price (premium) does not influence purchase decisions per se but does significantly influence quantity decisions. The quantity demanded is less price‐sensitive for subsequent rainfall insurance than it is for temperature insurance. We also find that purchasers of temperature insurance tend to buy rainfall insurance more often than nonpurchasers do. However, a one‐time subsidy does not influence on subsequent demand, suggesting no price‐anchoring effect.     

The impact of integrated aquaculture–agriculture on small-scale farms in Southern Malawi

Sustainable agricultural intensification is an urgent challenge for Sub-Saharan Africa. One potential solution is to rely on local farmers' knowledge for improved management of diverse on-farm resources and integration among various farm enterprises. In this article, we analyze the farm-level impact of one recent example, namely the integrated aquaculture–agriculture (IAA) technologies that have been developed and disseminated in a participatory manner in Malawi. Based on a 2004 survey of 315 respondents (166 adopters and 149 nonadopters), we test the hypothesis that adoption of IAA is associated with improved farm productivity and more efficient use of resources. Estimating a technical inefficiency function shows that IAA farms were significantly more efficient compared to nonadopters. IAA farms also had higher total factor productivity, higher farm income per hectare, and higher returns to family labor.     

Self‐protection from weather risk using improved maize varieties or off‐farm income and the propensity for insurance

We investigate how self‐protection from the adoption of Improved Maize Varieties (IMV) and off‐farm income affects risk premiums for smallholder maize producers in Uganda. To unbundle these effects, we specify the cost of risk to explicitly capture four risk components—mean, variance, skewness, and kurtosis. Using unique plot‐level panel data for Uganda, we estimate and test moments of a flexible production function based on an expanded form of the Johnson S_U family distribution and proceed to simulate the degree of responsiveness of risk premiums and welfare estimates to marginal changes in the share of land under IMV and off‐farm income. Scenarios of joint adoption of IMV accompanied with low and high application of inorganic fertilizer, and the effect of off‐farm income when there is high and low supply of farm labor are examined. Results show that the use of IMV and off‐farm income substantially reduces risk premiums and the individual effect is much higher under low fertilizer application and high supply of farm labor, respectively. Thus implying that self‐protection is likely to reduce the propensity for index insurance especially if its design fails to consider the reduction in downside risk.     

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.     

Horticulture exports, agro-industrialization, and farm–nonfarm linkages with the smallholder farm sector: evidence from Senegal

In this article we address the question of farm–nonfarm linkages at the household level in Senegal. We examine whether increasing off-farm employment opportunities for rural households—resulting from increased horticulture exports and associated agro-industrialization—has benefitted the smallholder farm sector through investment linkages. We use data from a household survey in the main horticulture export region in Senegal. We find that access to unskilled employment in the export agro-industry has contributed to the alleviation of farmers' liquidity constraints, resulting in increased smallholder agricultural production.     

Analyzing technology adoption using microstudies: limitations, challenges, and opportunities for improvement

Policy makers and interest groups have many questions about the use of improved technologies in developing country agriculture. These include the roles of policies, institutions, and infrastructure in the adoption of improved technologies and their impact on productivity and welfare. Most micro‐level adoption studies, however, cannot address these important policy issues. Drawing on an extensive review of the literature on the adoption of agricultural technologies, this article suggests alternative approaches for designing technology adoption studies to make them useful for policy makers. It explores the generic limitations of cross‐sectional adoption studies carried out in small numbers of communities and discusses some problems faced in conducting such studies. Recommendations include the use of sampling approaches that allow data from microstudies to be generalized to higher levels of aggregation, adherence to clearly defined terms that are standardized across studies, and careful examination of the assumptions that often underlie such studies.     

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.     

Valuing animal genetic resources: a choice modeling application to indigenous cattle in Kenya

In an effort to improve productivity and profits, many farmers have replaced traditional livestock breeds with higher yielding alternatives. While such changes may bring about short‐term economic gains, the loss of traditional livestock breeds could result in the loss of an important genetic resource as a variety of important genetic traits adapted to local conditions gradually become less common in the population. This is a particular problem in Africa, where livestock make a substantial contribution to human livelihoods. Using the example of cattle in Kenya's pastoral livestock markets this study uses a choice experiment approach to investigate buyers' preferences for indigenous breeds such as the Maasai Zebu. The analysis employs a latent class approach to characterize heterogeneity in valuations both within and across respondents buying cattle for breeding, slaughter, or resale. The results show that there are at least three classes of buyers with distinct preferences for cattle traits and that most buyers favor exotic rather than indigenous breeds. Such preferences have implications for the conservation of indigenous cattle in Kenya and in other developing countries and suggest that some form of intervention may be required to ensure the preservation of this important animal genetic resource.     

Heterogeneous information exposure and technology adoption: the case of tissue culture bananas in Kenya

Classical innovation adoption models implicitly assume homogenous information flow across farmers, which is often not realistic. As a result, selection bias in adoption parameters may occur. We focus on tissue culture (TC) banana technology that was introduced in Kenya more than 10 years ago. Up till now, adoption rates have remained relatively low. We employ the average treatment effects approach to account for selection bias and extend it by explicitly differentiating between awareness exposure (having heard of a technology) and knowledge exposure (understanding the attributes of a technology). Using a sample of Kenyan banana farmers, we find that estimated adoption parameters differ little when comparing the classical adoption model with one that corrects for heterogeneous awareness exposure. However, parameters differ considerably when accounting for heterogeneous knowledge exposure. This is plausible: while many farmers have heard about TC technology, its successful use requires notable changes in cultivation practices, and proper understanding is not yet very widespread. These results are also important for other technologies that are knowledge‐intensive and require considerable adjustments in traditional practices.     

Are small‐scale rice farmers in eastern India really inefficient? Examining the effects of microtopography on technical efficiency estimates

The article analyzes how controlling for differences in land types (defined by position on a low‐scale toposequence) affects estimates of farm technical efficiency for rice farms in eastern India. Contrasting previous research, we find that farms are considerably more technically efficient when efficiency estimates are carried out at the plot level and control for plot characteristics rather than at the farm level without such controls. Estimates show farms cultivating modern varieties are technically efficient and plots planted with traditional varieties on less productive lands (upland and midupland) operate close to the production frontier. Significant technical inefficiency is found on more productive lands (medium and lowland plots) planted with traditional rice varieties. The finding that these smallholder rain‐fed rice farms are efficient cultivators on some plots contrasts with previous findings of farm‐level inefficiency (i.e., rejects overarching explanations linked to farm operator ignorance or lack of motivation) and suggests more complex explanations are required to address the inefficiency that is present.     

Sustainable agricultural intensification practices and cost efficiency in smallholder maize farms: Evidence from Ethiopia

Sustainable agricultural intensification (SAI) practices have been promoted in developing countries to improve farm productivity and environmental services. However, it is still unclear whether use of a combination of SAI practices has a significant influence on the cost efficiency of smallholder farms. This study investigates whether the cost efficiency of smallholder maize producers in Ethiopia depends on use of input-augmenting and agronomic SAI practices. Stochastic cost frontier models that account for heterogeneity across farms are used for estimation. We find that the use of individual SAI practices increases cost while the combined use of the practices reduces it. The marginal effect on cost reduction is substantial when SAI practices are set at their sample maximum levels. Overall, the results demonstrate the benefit of using a combination of SAI practices in minimizing production cost while addressing the adverse effects of soil degradation and climate variability. To enhance food security, smallholder farm incomes and the sustainability of production in developing countries, policy programs should focus on promoting packages of input-augmenting and agronomic SAI practices.     

Estimating consumer willingness to pay for food quality with experimental auctions: the case of yellow versus fortified maize meal in Kenya

Biofortification of maize with provitamin A carotenoids is a new approach to the alleviation of vitamin A deficiencies in Africa. Unfortunately these varieties are yellow or orange, while consumers generally prefer white. Consumer willingness to pay for yellow and fortified maize was compared in experimental auctions in three regions in Kenya. The premium that consumers are willing pay for fortified maize (24%) was higher than the discount they require to buy yellow maize (11%), and in one zone consumers prefer yellow. Yellow color is, therefore, not an impossible obstacle for biofortified maize, although it would clearly be easier to introduce this maize first in regions where yellow maize is currently grown.     

Ex post impacts of improved maize varieties on poverty in rural Ethiopia

Public agricultural research has been conducted in Africa for decades. While many studies have examined its aggregate impacts, few have investigated how it affects the poor. This paper helps fill this gap by applying a new procedure to explore the ex post impacts of improved maize varieties on poverty in rural Ethiopia. Plot‐level yield and cost changes due to adoption are first estimated using instrumental variable and marginal treatment effect techniques where possible heterogeneity is carefully accounted for. A backward derivation procedure is then developed to link treatment effect estimates with an economic surplus model to identify the counterfactual household income that would have existed without improved maize varieties. Poverty impacts are finally estimated by exploiting the differences between observed and counterfactual income distributions. Improved maize varieties have led to a 0.8–1.3 percentage drop of poverty headcount ratio and relative reductions of poverty depth and severity. However, poor producers benefit the least from adoption due to the smallness of their land holdings.