Adoption of farm‐based irrigation water‐saving techniques in the Guanzhong Plain,China

This article analyses adoption of farm‐based irrigation water saving techniques, based on a cross‐sectional data set of 357 farmers in the Guanzhong Plain, China. Approximately 83% of the farmers use at least one farm‐based water‐saving technique. However, the traditional, inefficient techniques border and furrow irrigation are still prevalent whereas the use of advanced, more efficient techniques is still rather rare. We develop and estimate an adoption model consisting of two stages: awareness of water scarcity and intensity of adoption. We find that awareness of water scarcity and financial status enhance adoption of more advanced techniques whereas access to better community‐based irrigation infrastructure discourages it. We furthermore find both community‐based irrigation infrastructure and farm‐based irrigation water‐saving techniques have mitigating effects on production risk. From the results it follows that adoption can be stimulated via financial support and via extension aimed at enhancing awareness of water scarcity.     

Modeling the length and shape of the R&D lag: an application to UK agricultural productivity

This article updates total factor productivity (TFP) growth in UK agriculture from 1953–2005 and shows that public and private research and returns to scale explain TFP. Cointegration and causality tests are used to investigate the validity of attempts to explain UK agricultural productivity with R&D and related technology variables. Then, the length and shape of the lag structures are modeled and compared with the structures that are commonly imposed on the data. The rates of return (ROR) to R&D using the data determined lags differ considerably from those obtained by imposing lag shapes. These comparisons show that the ROR to public R&D are sensitive to the lag shape as well as its length and that the omission of other technology variables, such as mechanical and chemical patents pertaining to agriculture and farm size can bias the ROR.     

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.     

Adoption and welfare impacts of multiple agricultural technologies: evidence from eastern Zambia

Using plot level panel data and multinomial endogenous switching regression, this article analyzes the adoption and welfare impacts of multiple agricultural technologies in eastern Zambia. We adapt a multinomial endogenous switching/treatment effect regression framework to correct for selection bias and endogeneity originating from both observed and unobserved heterogeneity. Results indicate that joint adoption of multiple agricultural technologies had greater impacts on crop yields, household incomes, and poverty than the adoption of individual components of the technology package. Our findings suggest that efforts aimed at raising household incomes and reducing poverty should focus on promoting the adoption of multiple agricultural technologies through provision of improved support services such as extension and input supply.     

Tradeoffs and complementarities in the adoption of improved seeds,fertilizer, and natural resource management technologies in Kenya

There is widespread consensus that agricultural technology has an important role to play for poverty reduction and sustainable development. There is no consensus, however, about the types of technologies that are best suited for smallholder farmers in Africa. While some consider natural resource management (NRM) technologies as most appropriate, others propagate input intensification with a stronger role of the private sector. In the public debate, these two strategies are often perceived as incompatible. Environmental non‐governmental organizations in particular consider low‐external input strategies as the only sustainable form of agriculture, a view that has considerable influence on policymakers and the international donor community. Most existing research studies on smallholder innovation focus on the adoption of individual technologies, so that comparisons between different types of technologies in the same context are not easily possible. We use representative data from maize‐producing households in Kenya and a multivariate probit model to analyze the adoption of different types of technologies simultaneously. Results indicate that NRM technologies and strategies that build on external inputs are not incompatible. Interesting complementarities exist, which are not yet sufficiently exploited because many organizations promote either one type of technology or the other, but rarely a combination of both.     

Agent‐based modeling for ex ante assessment of tree crop innovations: litchis in northern Thailand

This study uses an agent‐based model for ex ante assessment of agricultural innovations. The model builds on whole farm mathematical programming (MP) and extends the methodology with a spatial representation of the system, the heterogeneity of farm households and landscapes, and the interaction between farm households. We apply the model in a northern Thai watershed to study the potential of four innovations to increase the profitability of litchi orchards. Cost‐benefit analysis shows that each innovation would increase the profitability of litchi growing; however, the results of the agent‐based model show that at current price levels these innovations alone would not be enough to stem the decline in the area under litchis. The model was validated and the sensitivity of the results tested for variations in the irrigated water supply and liquidity. We report on how farmers responded to these results and discuss the implications for other areas in northern Thailand.     

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.     

Mobile money,agricultural marketing,and off‐farm income in Uganda

Mobile money (MM) services can contribute to welfare gains in smallholder farm households. Previous research showed that one important pathway for these MM‐related welfare gains is through higher remittances received from relatives and friends. Here, the role of other impact pathways is examined, especially focusing on agricultural marketing and off‐farm economic activities. The analysis builds on panel data from smallholder coffee farmers in Uganda. Regression models show that the adoption of MM technology has contributed to higher household incomes and consumption levels. Off‐farm income gains are identified to be an important pathway, also beyond remittances. Typical off‐farm income sources are small businesses in trade, transport, and handicrafts, which benefit from novel savings and money transfer opportunities through MM. In terms of agricultural marketing, MM users sell a larger proportion of their coffee as shelled beans to buyers in high‐value markets, instead of selling to local traders immediately after harvest. MM services help to reduce cash constraints and facilitate transactions with buyers from outside local regions. In conclusion, MM can contribute to rural development through various important pathways. Analysis of adoption patterns suggests that MM services are socially inclusive.     

Yield and income effects of rice varieties with tolerance of multiple abiotic stresses: the case of green super rice (GSR) and flooding in the Philippines

With the increasing frequency of extreme climatic events, the new challenge is to develop rice varieties that are tolerant of drought, water submergence, and salinity. There are now new high‐yielding green super rice (GSR) cultivars developed at the International Rice Research Institute with increased tolerance to multiple abiotic stresses. But a clear understanding of the economic benefits of these varieties under farmers’ production environments is not yet fully understood. In this article, we assess the yield and income effects of GSR rice varieties using a two‐year panel data from one province. We use matched samples from a propensity score matching method and a fixed‐effects model within a difference‐in‐difference (DID) framework to estimate the yield effects. The income effects were evaluated using the parameter estimates from the yield/production function model. The results of the ordinary least squares and DID fixed‐effects regressions reveal significant and positive effects of GSR varieties on yield. The most important finding is that the benefits from these varieties are strongly felt when there is flooding. This evidence was not as robust when matched samples were used. However, it is clear that the yield benefits from GSR varieties could improve rice food security and help alleviate poverty in the country.     

When knowledgeable neighbors also share seedlings: diffusion of banana cultivation in Tanzania

Networks have been found to increase adoption of technology by providing information about the new technology (e.g., Conley and Udry, 2010). However, little is known about provision of necessary inputs for adoption through networks. Using data from an intervention in Tanzania, I discuss how a farmer's network can also affect the adoption of improved banana cultivation by providing seedlings. A solidarity chain principle obliged project farmers to pass on improved seedlings to other farmers free of charge. I provide a theoretical framework to guide intuition for the empirical results and suggest an empirical distinction between information and input provision through networks. Empirically, I find support for network effects through provision of both information and inputs, jointly boosting the network effect on adoption: a farmer is 39 percentage points more likely to adopt banana cultivation if there is at least one banana grower in the farmer's network compared to none. In this setting, it is not possible to fully disentangle the input and information channel. While the findings suggest that a solidarity chain principle could be an interesting avenue to boost local diffusion of new technologies, more research is needed to unpack the causal impact and the interplay with existing input markets.     

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.     

Modelling the Crop Variety Demand of Semi‐Subsistence Households: Bananas in Uganda

We propose an approach to model the derived demand for crop varieties among semi‐subsistence farmers in a developing economy, and apply it to smallholder banana producers in Uganda. We model variety planting decisions as being composed of an extensive margin decision to grow a subset of locally available varieties (variety choice); and an intensive margin decision about the scale or extent of variety cultivation per farm (variety demand). We estimate variety demand equations using a more complete representation of the choice set upon which observed planting decisions are made. Computed elasticities of variety demand with respect to variety attributes indicate that the relative importance of consumption and production attributes varies by location and proximity to markets, from which we draw implications for the social and economic impact of crop improvement. The approach that we propose has broad appeal for analysing adoption decisions for modern or traditional varieties of both major and minor crops in developing countries.     

Economywide effects of climate‐smart agriculture in Ethiopia

Climate‐smart agriculture (CSA) is an approach for transforming and reorienting agricultural systems to support food security under climate change. Few studies, however, quantify at the national scale CSA's economic effects or compare CSA to input‐intensive technologies, like fertilizer or irrigation. Such quantification may help with priority setting among competing agricultural investment options. Our study uses an integrated biophysical and economic modeling approach to quantify and contrast the economywide effects of CSA (integrated soil fertility management in our study) and input‐intensive technologies in Ethiopia's cereal systems. We simulate impacts for 20‐year sequences of variable weather, with and without climate change. Results indicate that adopting CSA on 25% of Ethiopia's maize and wheat land increases annual gross domestic product (GDP) by an average 0.18% (US$49.8 million) and reduces the national poverty rate by 0.15 percentage points (112,100 people). CSA is more effective than doubling fertilizer use on the same area, which increases GDP by US$33.0 million and assists 75,300 people out of poverty. CSA and fertilizer have some substitutability, but CSA and irrigation appear complementary. Although not a panacea for food security concerns, greater adoption of CSA in Ethiopia could deliver economic gains but would need substantial tailoring to farmer‐specific contexts.     

The role of nonfarm income in coping with the effects of drought in southern Mozambique

To reduce their dependence on subsistence agriculture, farm households in rural Africa may diversify their income sources by participating in the nonfarm sector. In years of drought, nonfarm income can also be part of the coping strategies. A multivariate sample selection model was used to analyze three years of data from a nationally representative household survey in Mozambique. The analysis was guided by the following three questions. During a drought year: (1) Do households increase their participation in nonfarm activities? (2) Are poorer households as likely as others to participate in and benefit from nonfarm activities? and (3) Which factors are associated with higher nonfarm incomes? The results suggest that households are more likely to engage in at least one nonfarm income‐generating activity during a drought year. Although poorer households are more likely to engage in nonfarm activities, they are less likely to participate in nonfarm activities of high return. The results suggest that policies reducing entry barriers (e.g., improved road infrastructure, micro‐credit schemes, and livestock promotion programs) and increasing education levels can facilitate income diversification, thus allowing rural households to better cope with the effects of drought. When designing polices, care must be taken to avoid exacerbating income inequality by targeting measures toward poorer and female‐headed households.     

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.     

Impact of training on the intensification of rice farming: evidence from rainfed areas in Tanzania

Agricultural development is indispensable for poverty reduction and food security in sub‐Saharan Africa (SSA). This study investigates the impact of rice production training in a modified version of the System of Rice Intensification (SRI) on the performance of small‐scale rice farmers in a rainfed area of Tanzania. Utilizing the plot level variation, we employ propensity score matching (PSM) to assess the impact of training on technology adoption, productivity, and profitability. We also estimate a difference‐in‐differences model with plot fixed effects using recall panel data covering the periods before and after training. We found that trainees achieved an average paddy yield of 4.7 tons per hectare and rice profit of 191.5 USD per hectare on the plots where new technologies were adopted, which is higher by about 1.3–1.8 tons and 119–137 USD per hectare than on the other plots. Our study suggests the high potential of transforming favorable rainfed rice growing areas in SSA so as to achieve a rice Green Revolution through training in modern input use and improved agronomic practices.     

Structural Change of European Dairy Farms – A Cross‐Regional Analysis

Previous analyses of dairy farm structural change focus on the variation over time in one or a small number of regions. We present an EU‐15 cross‐regional analysis of the development of dairy farm numbers in different size classes over the period 1995–2005. Our purpose is to measure the explanatory relevance and effect of key factors suggested in the theoretical and empirical literature on structural change. Apart from the unprecedented scope, the underlying Markov chain analysis also contributes by combining observed transitions in micro (farm level) data with macro (sector level) data on farm numbers. Results show widely significant impacts of most considered explanatory variables, but also reflect and illuminate the complexity of the underlying processes.     

O‐Ring production on U.S. hog farms: joint choices of farm size,technology, and compensation

We hypothesize that hog production can be characterized by complementarities between new technologies, worker skills, and farms size. Such production processes are consistent with Kremer's O‐ring production theory in which a single mistake in any one of several complementary tasks in a firm's production process can lead to catastrophic failure of the product's value. In hog production, mistakes that introduce disease or pathogens into the production facility can cause a total loss of the herd. Consistent with predictions derived from the O‐ring theory, we provide evidence that the most skilled workers concentrate in the largest and most technologically advanced farms and are paid more than comparable workers on smaller farms. These findings suggest that worker skills, new technologies, and farm size are complements in production. The complementarities create returns to scale to large hog confinements, consistent with the dramatic increase in market share of very large farms over the past 20 years.     

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.     

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.