How does gender affect the adoption of agricultural innovations?

Why do men and women adopt agricultural technologies at different rates? Evidence from Ghana suggests that gender‐linked differences in the adoption of modern maize varieties and chemical fertilizer result from gender‐linked differences in access to complementary inputs. This finding has important policy implications, because it suggests that ensuring more widespread and equitable adoption of improved technologies may not require changes in the research system, but rather introduction of measures that ensure better access for women to complementary inputs, especially land, labor, and extension services.     

The adoption of intensive monocrop horticulture in southern Cameroon

Results from a 1997 survey of 208 households in the humid forest zone of southern Cameroon indicate that African policy makers seeking to intensify agricultural production should focus attention on the horticultural sub‐sector. The survey, which gathered information on horticultural production practices, found that the average expenditure on agro‐chemical inputs by horticultural producers using monocrop production systems was 190US$/ha, which greatly exceeds the FAO reported national average expenditure of 6.50 US$/ha. A logit model of monocrop adoption indicated that the size of land holding per household had a negative effect on adoption, congruent with population‐driven technical change and that increases in unit transportation costs significantly decreased the probability of adoption. These findings suggest that policy makers should target horticultural intensification in areas of higher population density and promote investment in rural roads. The age of the household head had a significant negative and elastic effect on adoption, which in combination with an increase in the cohort of younger farmers in the rural population induced by macro‐economic events contributed to the spread of intensified horticulture. In the study area, roughly two‐thirds of rural households also produce cocoa and the quantity of cocoa produced was positively associated with adoption of intensive horticultural systems suggesting that export crop promotion indirectly facilitated diversification of agriculture. Women's participation in intensive monocrop production was limited and efforts to promote their greater involvement are recommended.     

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.     

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.     

Agricultural diversification and integrated pest management in Bangladesh

We study factors associated with a shift toward diversified, high‐valued vegetable crops and the incentives associated with the use of IPM methods for vegetable producers in Bangladesh. The primary objective is to measure how IPM technologies affect the crop and technology choices of low‐income rice farmers. A three‐season household optimisation model is used to study crop and technology choice under price and yield uncertainty. The model is parameterised using data from vegetable farms and experimental IPM trials conducted in Bangladesh. Simulation results show that access to IPM technology and IPM availability combined with access to credit increase household welfare and lead to higher rates of vegetable adoption. Off‐farm employment opportunities work against vegetable cultivation and IPM use by risk‐averse farmers. Implications for policy and extension efforts are highlighted.     

Land titling policy and soil conservation in the northern uplands of Vietnam

In Vietnam, a quasi-private property regime has been established in 1993 with the issuance of exchangeable and mortgageable long-term land use right certificates. Using primary qualitative and quantitative data collected in a mountainous district of Northern Vietnam, this paper investigates the role of the land policy in the adoption of soil conservation technologies by farmers. This issue is of crucial importance in the region where population growth and growing market demands have induced farmers to intensify agricultural production. While poverty has been reduced, environmental problems such as soil erosion, landslides, and declining soil fertility have become more severe over the past years. Our findings suggest that despite farmers’ awareness of erosion, soil conservation technologies are perceived as being economically unattractive; therefore, most upland farmers continue to practice the prevailing erosion-prone cultivation system. Focusing on agroforestry as one major soil conservation option, we estimate household and plot-level econometric models to empirically assess the determinants of adoption. We find that the possession of a formal land title positively influences adoption, but that the threat of land reallocations in villages discourages adoption by creating uncertainty and tenure insecurity. The analyses reveal that these two effects interact with each other but are of small magnitude. We conclude that the issuance of land titles is a necessary but not sufficient prerequisite to encouraging the adoption of soil conservation practices. However, current practices remain economically unattractive to farmers. This deficiency needs to be addressed by interdisciplinary research and complemented by strong efforts by local authorities to promote sustainable land use.     

The fourth industrial revolution,agricultural and rural innovation,and implications for public policy and investments: a case of India

The Indian Government and public–private partnerships are developing and disseminating a dizzying number of innovative, networked solutions, broadly known as the Digital India initiative, to increase the efficiency of safety nets and worker productivity and to improve life. Yet, challenges to turn the power of information and other technologies into a farmer‐friendly technological revolution for India's 156 million rural households are considerable, including: (1) reliable, up‐to‐date, location‐specific message content for a diverse agriculture to help stratified households shift to productive, knowledge‐intensive agriculture as a business—government, private sector, and civil society have big roles to play; (2) digital literacy, i.e., teaching farmers how to choose and use apps, even where the digital divide is absent; apps are, or soon to be, in regional languages; and (3) monitoring actual use and impacts on users’ lives by understanding the adoption and adaptation processes. These challenges call for bottom‐up, complementary investments in physical, human, and institutional capital, and farmer‐friendly e‐platforms, while forging ahead with many top‐down policy and institutional reforms currently underway, in which progress is real and constraints holding back greater success are better understood.     

Policies for sustainable development in the hillside areas of Honduras: a quantitative livelihoods approach

In this article, we use data for 376 households, 1,066 parcels, and 2,143 plots located in 95 villages in the hillside areas in Honduras to generate information needed by decision makers to assess the needs and opportunities for public investments, and design policies that stimulate natural resource conservation. We develop a quantitative livelihood approach, using factor and cluster analysis to group households based on the use of their main assets. This resulted in seven household categories that pursue similar livelihood strategies. We use a multinomial logit model to show that livelihood strategies are determined by comparative advantages as reflected by a combination of biophysical and socioeconomic variables. While 92% of the rural hillsides population in Honduras lives on US$1.00/capita/day or less, households that follow a livelihood strategy based on basic grain farming are the poorest because they often live in isolated areas with relatively poor agro‐ecological and socioeconomic conditions. Opportunities for off‐farm work tend to be limited in these areas and household strategies that combine on‐farm work with off‐farm work earn higher incomes. Per capita incomes can be increased by improving road infrastructure, widening access to land, policies that reduce household size and dependency ratios, and adoption of sustainable land management technologies that restore soil fertility. We used probit models to show that the latter can be promoted by agricultural extension programs and land redistribution. Investments in physical assets should be directed toward households that pursue livelihood strategies based on off‐farm employment or coffee production, while agricultural training programs are best focused on livestock producers.     

The economic impact of cowpea research in Senegal: an ex-post analysis with disadoption

This study evaluates the impact of a long‐term research collaboration between the Senegalese Institute for Agriculture Research (ISRA), and the Bean/Cowpea Collaborative Research Support Program (CRSP) funded by the U.S. Agency for International Development (USAID). Adoption of the primary outputs from this collaboration, a nonchemical cowpea storage method and two short‐season cowpea varieties, were tracked through a series of farmer interviews in 1996, 1997, and 2004 in the main cowpea growing area of Senegal. Combined with information from an impact assessment in the late 1980s, this study draws on ex‐post adoption data from most of the product life cycle for the storage technology. The 2004 survey found that 60.4% of cowpea production in the main cowpea growing area of Senegal is stored in metal drums and that 69% of households use this storage technology; ISRA/CRSP improved short season varieties were determined to account for 3.6% of cowpea production. Baseline economic analysis of the most recent survey data, which includes benefits and costs of the storage technology and improved varieties, reveal an IRR to donor funding of 13%. The benefits of these technologies appear to be evenly distributed in the rural population on the basis of gender and ethnic background. Comparison of the rates of technology adoption over time, however, reveals that use of the storage technology may be decreasing; inclusion of this technology disadoption trend reduces the IRR by only 0.4% from the baseline estimate. Overall, estimated returns reveal that this collaboration has been a good investment for the U.S. and Senegalese governments, and other donors.     

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.     

Adding value to spatially managed inputs by understanding site-specific yield response

Many mechanized crop producers and agribusinesses are fascinated with precision agriculture technology, but adoption has lagged behind the expectations. Among the reasons for slow adoption of precision agriculture technology is that initial users focused excessively on in‐field benefits from variable‐rate fertilizer application using regional average fertilizer recommendations. This article illustrates how greater use of site‐specific crop response information can improve variable rate input application recommendations. Precision agriculture is spatial information technology applied to agriculture. The technologies include global position systems (GPS), geographic information systems (GIS), yield monitoring sensors, and computer controlled within‐field variable rate application (VRA) equipment. Experimentation with these technologies is occurring everywhere there is large scale mechanized agriculture. Commercial use has been greatest in the US, where 43% of farm retailers offered VRA services in 2001. Except for certain high‐value crops like sugar beet, farmer adoption of VRA has been modest. The farm level profitability of VRA continues to be questionable for bulk commodity crops. The theoretical model and illustration presented here suggest that VRA fertilization has not yet reached its profitability potential. Most VKA field trials to date have relied upon existing state‐wide or regional input rate recommendations. Unobserved soil characteristics can potentially interact with an input to make its effect on yield vary site‐specifically within fields. Failure to use site‐specific response functions for VRA applications may lead to a misallocation of inputs just as great as that which results from using uniform applications instead of VRA. Agricultural economists have a long history of estimating output response to input applications. Several have started to develop tools to estimate site‐specific responses from yield monitor and other precision agriculture data. Likewise, agricultural economists have developed an important body of research results on information value based on managing variability—typically in temporal settings. With these tools, a major potential exists to develop further benefits from precision agriculture technologies that permit truly spatially tailored input applications.     

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 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.     

An interdisciplinary approach to regional land use analysis using GIS, with applications to the Atlantic Zone of Costa Rica

Policy makers and other stakeholders concerned with regional rural development increasingly face the need for instruments that can improve transparency in the policy debate and that enhance understanding of opportunities for and limitations to development. To this end, a methodology called SOLUS (Sustainable Options for Land Use) was developed by an interdisciplinary team of scientists over a 10-year period in the Atlantic Zone of Costa Rica. The main tools of SOLUS include a linear programming (LP) model, two expert systems that define technical coefficients for a large number of production activities, and a geographic information system (GIS). A five-step procedure was developed for GIS to spatially reference biophysical and economic parameters, to create input for the expert systems and the LP model, to store and spatially reference model output data, and to create maps of both model input and output data. SOLUS can be used to evaluate the potential effects of alternative policies and incentive structures on the performance of the agricultural sector. A number of practical applications demonstrate SOLUS's capability to quantify trade-offs between economic objectives (income, employment) and environmental sustainability (soil nutrient balances, pesticide use, greenhouse gas emissions). GIS-created maps visualize the spatial aspects of such trade-offs and indicate hotspots where local goals may conflict with regional goals.     

Early adoption,experience, and farm performance of GM corn seeds

The current article explores the characteristics that distinguish early from late adopters of GM corn and measures the productivity impacts of early adoption, for a sample of farmers in Minnesota and Wisconsin. The results of the adoption analysis confirm that size, education as well as specialization are positively correlated with early adoption. In addition, these results also show that farms that are mostly worked by family labor but hire some off‐farm labor are more likely to adopt GM seeds earlier in the diffusion process. The productivity analysis demonstrates the superiority of stacked varieties. At the same time, we find no evidence of a direct impact of experience on yields. Given the previously documented impact of early adoption on the use of stacked varieties, we conclude that experience plays a role through the adoption of these new technologies but does not play a role in allowing the producer to use the technology more efficiently, once it has been adopted.     

Risk, uncertainty, and learning in adoption of a crop innovation

Risk and uncertainty have often been suggested as causes of poor adoption of rural innovations, but empirical evidence has been scarce. This study focuses on a new crop‐type, chickpeas, in Western Australia to gather such evidence. The empirical models developed are based on a theoretical framework that conceptualizes adoption as a dynamic decision process involving information acquisition and learning‐by‐doing by growers who vary in their managerial abilities, risk preferences, and their perceptions of the profitability and riskiness of the innovation. Learning encompasses improvements in skill as well as reductions in uncertainty. An annual face‐to‐face survey of over 100 farmers was conducted over 3 years, eliciting the farmers' risk attitudes and their subjective distributions of yields and prices. Two limited dependent variable models, Tobit and Probit, are used to estimate the empirical model. There is a high degree of goodness‐of‐fit for both models. The study provides strong empirical support for the primarily economic character of the adoption decision, and highlight the importance of economic risk in the process. The two risk‐related factors with greatest impact on the adoption decision were risk aversion and relative riskiness of the innovation. Risk aversion tended to reduce adoption, and to do so to a greater extent as relative riskiness and scale increased. Results also reveal the key role that trialing of the innovation plays in adoption.     

Roundup Ready soybeans in Argentina: farm level and aggregate welfare effects

Although adoption rates of genetically modified crops have been staggering in some countries, there is still comparatively little evidence about biotechnology impacts under diverse agroecological and institutional conditions. These knowledge gaps lead to an overly precautious attitude among policy makers and the public. This article analyzes the effects of Roundup Ready (RR) soybeans in Argentina, the country with the second biggest transgenic area worldwide. Based on recent survey data, it is shown that the technology increases total factor productivity by 10% on average, with cost savings being somewhat more pronounced for smaller than for larger farms. The reduction in use of toxic herbicides and of tillage operations entails positive environmental repercussions. Aggregate welfare effects are computed over the 1996–2001 period with a three-region, partial equilibrium model, comprising Argentina, the United States, and the rest of the world. In 2001, RR soybeans created more than US$1.2 billion of economic surplus at the global level. The largest share went to consumers (53%), followed by seed and biotechnology firms (34%), and agricultural producers (13%). Due to comparatively weak intellectual property protection, and thus only small technology mark-ups in seed prices and widespread adoption, Argentine soybean growers receive 90% of the benefits in that country. This demonstrates that farmers in developing countries can gain considerably when they obtain access to suitable foreign innovations through technology spill-overs.     

A dynamic adoption model with Bayesian learning: an application to U.S. soybean farmers

Adoption of agricultural technology is often sequential, with farmers first adopting a new technology on part of their lands and then adjusting their use of the new technology in later years based on what was learned from the initial partial adoption. Our article explains this experimental behavior by using a dynamic adoption model with Bayesian learning, in which forward‐looking farmers take account of future impacts of their learning from both their own and their neighbors’ experiences with the new technology. We apply the analysis to a panel of U.S. soybean farmers surveyed from 2000 to 2004 to examine their adoption of the genetically modified (GM) seed technology. We compare the results of the forward‐looking model to that of a myopic model, in which farmers maximize current benefits only. Results suggest that the forward‐looking model fits data better than the myopic model does. And potential estimation biases arise when fitting a myopic model to forward‐looking decision makers.     

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.     

Soil and water conservation technologies: a buffer against production risk in the face of climate change? Insights from the Nile basin in Ethiopia

This study investigates the impact of different soil and water conservation (SWC) technologies on the variance of crop production in Ethiopia to determine the risk implications of the different technologies in different regions and rainfall zones. Given the production risks posed by climate change, such information can be used by decision makers to identify appropriate agricultural practices that act as a buffer against climate change. Results show that SWC investments perform differently in different rainfall areas and regions of Ethiopia and that the effectiveness of technologies such as irrigation, fertilizer, and improved seeds often depends on whether these investments are coupled with SWC measures. These results underscore the importance of the selection of appropriate combinations of technologies and careful geographical targeting when promoting and scaling up SWC technologies for adaptation to climate change.