Risk,learning, and technology adoption

This article explores how decision makers learn and use information, with an application to the adoption of biotechnology in agriculture. The empirical analysis relies on experimental and survey data measuring risk preferences, learning processes, and the adoption of genetically modified (GM) seeds among U.S. grain farmers. While controlling for risk aversion, we link individual learning rules with the cognitive abilities of each decision maker and their actual GM adoption decisions. We find evidence that very few individuals are Bayesian learners, and that the population of farmers is quite heterogeneous in terms of learning rules. This suggests that Bayesian learning (as commonly assumed in the analysis of agricultural technology adoption) is not an appropriate characterization. In addition, we do not find a strong relationship between observed learning styles and the timing of GM seed adoption. To the extent that learning is a key part of the process of technology adoption, this suggests the presence of much unobserved heterogeneity in learning among farmers.     

Social capital,risk preference and adoption of improved farm land management practices in Ethiopia

Many developing countries grapple with high rates of farmland degradation and low agricultural productivity amidst increasing climate variability. Considerable efforts have been exerted to promote the diffusion of improved farmland management to address these challenges. Despite these efforts, adoption rates, especially of soil conservation and water harvesting technologies, are still low, which has been the subject of investigation in several studies in Ethiopia and elsewhere. Most studies on the adoption of these technologies, however, tend to focus on economic incentives only, paying little attention to the role of social capital. This article provides evidence of the effects of different dimensions of social capital on innovation adoption across households holding different levels of risk aversion. We address this issue by using cross section and panel data from Ethiopia. Results show that social capital plays a significant role in enhancing the adoption of improved farmland management practices. We also find evidence that the effect of social capital across households with heterogeneous risk taking behavior is different.     

Information Barriers to Adoption of Agricultural Technologies: Willingness to Pay for Certified Seed of an Open Pollinated Maize Variety in Northern Uganda

We examine smallholder farmers’ willingness to pay for agricultural technology and whether information is a constraint to adoption of certified maize seed in Northern Uganda. The uptake of improved maize varieties by smallholder farmers in Uganda remains persistently low, despite the higher yield potential compared to traditional varieties. A recently growing body of literature identifies information constraints as a potential barrier to adoption of agricultural technologies. We used incentive compatible Becker‐DeGroot‐Marschak auctions to elicit willingness to pay for quality assured improved maize seed by 1,009 smallholder farmers, and conducted a randomised evaluation to test the effect of an information intervention on farmers’ knowledge of seed certification. Our results show that the randomised information treatment enhanced farmers’ knowledge of certified seed. However, using the information treatment as an instrumental variable for knowledge, we find no evidence of a causal effect of knowledge on willingness to pay, suggesting that even though farmers are information constrained, this constraint does not affect adoption of certified seed directly. Nevertheless, only 14% of sampled farmers were willing to pay the market price, which corresponds closely with actual observed demand for certified seed in the previous season. This suggests that there are other barriers to adoption than information and awareness.     

Social learning and technology adoption: the case of coffee pruning in Peru

A unique natural experiment involving a coffee pruning technology is used to study social learning. The yield effects of pruning take two years to appear, a characteristic that aids in identifying social learning apart from correlated unobservable variables that are a concern in the social learning and technology adoption literature. Panel data are employed that start with a private initiative which introduced systematic pruning in central Peru and that contain the population of participating growers. Results show a jump of at least 0.15 in the probability of adoption two years after the first pruning in a grower's group.     

Inducing the adoption of emerging technologies for sustainable intensification of food and renewable energy production: insights from applied economics*

Emerging advances in sustainable intensification technologies have the potential to transform land use and crop management approaches in ways that can increase resource productivity and reduce adverse environmental impacts of agricultural production. This paper describes emerging technologies that can sustainably intensify food and renewable energy production. We apply the findings from studies examining the adoption of technologies with similar stylized features to provide insights about the incentives and barriers for the adoption of these emerging technologies. We also present a landscape-based systems approach, based on welfare economics, to go beyond relying on a positive approach to explain observed adoption decisions to examining normative questions about the optimal mix, level, and location of adoption of these technologies to achieve desired societal outcomes. We conclude with a discussion of the insights from applied economics for the design of policy incentives to achieve these outcomes.     

Exploring the adoption of precision agricultural technologies: A cross regional study of EU farmers

Precision agricultural technologies (PATs) allow more detailed management of in-field variability. Policy and advisory communities have championed PATs as a route to preserving natural capital whilst increasing productivity from agricultural land. A range of PATs are currently available for the agricultural producer but uptake varies by the type of technology and region. Whereas most studies on uptake have focused on US or Australia we empirically examine uptake of machine guidance (MG) and variable rate nitrogen technologies (VRNT) within European farming systems. Using primary information from 971 arable crop growers across five countries: Belgium, Germany, Greece, the Netherlands and the UK, a multilevel random intercept regression estimated a) the differences between adoption and non-adoption and b) the differences between VRNT and MG adoption. We find, aside from size and income differences, which reflect the economic cost barrier to adoption, an attitudinal difference, in terms of optimism towards the technology’s economic return leading to more probability of uptake. Moreover innovative and information seeking behaviour also proved significant when upgrading from machine guidance to variable rate technologies. Subsidy and taxation were considered positive drivers of uptake within the community. However, results suggest that more indirect interventions, such as informational support to counteract industry bias, and demonstration to prove the viability of economic return may be effective at meeting land manager and policy expectations towards PATs.     

Oil Palm Expansion among Smallholder Farmers in Sumatra,Indonesia

Many tropical regions are experiencing a rapid growth of oil palm cultivation. In Indonesia, the world's leading palm oil producer, in addition to large companies, smallholder farmers are increasingly engaged in the oil palm sector. Smallholder oil palm cultivation may contribute to income gains and socio‐economic development. However, land‐use decisions by smallholders are not well understood. Without appropriate policies, negative social and environmental consequences can also occur. To improve the knowledge base, we use data about present and past land‐use decisions from a survey of farm households in Sumatra. Employing duration models, we analyse the determinants and dynamics of oil palm adoption among smallholders. We find that independently operating farmers are currently driving growth rates in the oil palm sector. Smallholder adoption decisions are mainly attributable to regional and village level factors. While the current adoption primarily occurs outside of contracts, previous contractual ties between companies and other farmers in the same village play an important role for individual decisions. Beyond initial adoption, we also analyse later expansion decisions. While expanding the oil palm area subsequent to initial adoption is common among all types of adopters, those without previous contracts are found to expand significantly faster. We conclude that the concessions the government has allocated to palm oil companies in the past have initiated oil palm adoption in the small farm sector, but that the ensuing land‐use dynamics are mostly beyond government control. Some wider implications are discussed.     

Poverty Reduction Effects of Agricultural Technology Adoption: The Case of Improved Cassava Varieties in Nigeria

We use DNA‐fingerprinting to estimate the poverty reduction effect of adoption of improved cassava varieties in Nigeria. We estimate the counterfactual household income distribution of cassava producers by combining farm‐level treatment effects with a market‐level model. Our results suggest that adoption of improved cassava varieties has led to a 4.6 percentage point reduction in poverty, though this is sensitive to the measurement of adoption status. Therefore, accurate measurement of adoption is crucial for a more credible estimate of the poverty reduction effect of adoption. Our analysis also suggests that farmers who are more likely to be adopters are also likely to face higher structural costs. Addressing structural barriers that make improved technologies less profitable for the poor would therefore be important to increase the poverty reduction effect of improved cassava varieties.     

Adoption of Multiple Sustainable Agricultural Practices in Rural Ethiopia

The adoption and diffusion of sustainable agricultural practices (SAPs) has become an important issue in the development‐policy agenda for sub‐Saharan Africa, especially as a way to tackle land degradation, low agricultural productivity and poverty. However, the adoption rates of SAPs remain below expected levels. This study analyses the factors that facilitate or impede the probability and level of adoption of interrelated SAPs, using recent data from multiple plot‐level observations in rural Ethiopia. Multivariate and ordered probit models are applied to the modelling of adoption decisions by farm households facing multiple SAPs, which can be adopted in various combinations. The results show that there is a significant correlation between SAPs, suggesting that adoptions of SAPs are interrelated. The analysis further shows that both the probability and the extent of adoption of SAPs are influenced by many factors: a household’s trust in government support, credit constraints, spouse education, rainfall and plot‐level disturbances, household wealth, social capital and networks, labour availability, plot and market access. These results imply that policy‐makers and development practitioners should seek to strengthen local institutions and service providers, maintain or increase household asset bases and establish and strengthen social protection schemes in order to improve the adoption of SAPs.     

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.     

Dial “A” for agriculture: a review of information and communication technologies for agricultural extension in developing countries

Agriculture can serve as an important engine for economic growth in developing countries, yet yields in these countries have lagged far behind those in developed countries for decades. One potential mechanism for increasing yields is the use of improved agricultural technologies, such as fertilizers, seeds, and cropping techniques. Public sector programs have attempted to overcome information‐related barriers to technological adoption by providing agricultural extension services. While such programs have been widely criticized for their limited scale, sustainability, and impact, the rapid spread of mobile phone coverage in developing countries provides a unique opportunity to facilitate technological adoption via information and communication technology (ICT)‐based extension programs. This article outlines the potential mechanisms through which ICT could facilitate agricultural adoption and the provision of extension services in developing countries. It then reviews existing programs using ICT for agriculture, categorized by the mechanism (voice, text, internet, and mobile money transfers) and the type of services provided. Finally, we identify potential constraints to such programs in terms of design and implementation, and conclude with some recommendations for implementing field‐based research on the impact of these programs on farmers’ knowledge, technological adoption, and welfare.     

Irrigation Technology Adoption and Gains from Water Trading under Asymmetric Information

We develop a water allocation and irrigation technology adoption model under the prior appropriation doctrine with asymmetric information among heterogeneous farmers and between farmers and water authorities. We find that adverse selection reduces the adoption of modern irrigation technology. We also show that even with asymmetric information, incentives for water trade exist and lead to additional technology adoption with gains to all parties. This suggests that under asymmetric information, a thin secondary market improves the allocation of water resources and induces additional adoption of modern irrigation technologies.     

Advancing climate-smart-agriculture in developing drylands: Joint analysis of the adoption of multiple on-farm soil and water conservation technologies in West African Sahel

Water stress and soil infertility are the greatest constraining factors for higher agricultural productivity in drylands, prompting the current interest in soil and water conservation (SWC) practices in water-constrained regions. To provide a more comprehensive understanding of challenges surrounding the adoption of SWC practices in these regions, we used a joint analysis framework combining both multivariate and ordered probit models to analyze adoption-decisions for eleven on-farm SWC practices. Our case study, involving 500 farmers from a representative West African Sahelian zone, revealed that although the adoption of SWC practices is widespread in the West African drylands, there is still an important potential to improve and upscale their specific adoption rates. Almost all farmers (99%) used at least one of the eleven practices considered in this study, whereas specific adoption rates ranged from 5% for contour vegetation barriers to 87% for manure application. More than 70% of the farmers used up to three practices only, and less than 30% used between four to nine practices. Many practices are interdependent, with some practices being complementary and others substitutable. The analysis of the determinants of the adoption and the intensity of adoption revealed that SWC practices are labor-, knowledge- and capital-intensive. We found that the major drivers of farmers’ decisions to adopt, as well as to intensify the use of, most SWC practices are the presence of children (aged 6 to 14) in the household, land holding, land tenure, awareness and training on SWC and access to alternative – but non-agricultural labor constraining – cash sources such as remittance and cash farming. A higher number of migrating household members increases the probability of intensifying the use of SWC practices, but only when this is in line with the household’s land endowment and labor needs for farm activities. This comprehensive study will be of significance for a finer understanding of SWC practices in West African Sahel. More generally, it will likely help policy makers to upscale the adoption of sustainable SWC practices for the advance of climate-smart agriculture in developing drylands.     

Climate-resilient practices and welfare impacts on rice-cultivating households in Vietnam: Does joint adoption of multiple practices matter?

Farmers have a long history of adjusting their production practices in response to changing production conditions. Using a multinomial endogenous treatment effects model that accounts for observable and unobservable heterogeneity, this study investigates the adoption and welfare impacts of climate-resilient practices on Vietnamese rice-cultivating households. We found evidence of clear and positive welfare impacts from the adoption of canal irrigation (CI) and the joint adoption of agricultural conservation practices (CP) and CI as the main adaptation strategies to increase water stress. More importantly, although farmers with access to CI systems obtained the highest returns, the joint adoption of multiple practices still had substantially high adoption rates and significantly positive effects on rice yield, rice revenue and household income. Our findings indicate that farms' and farmers' characteristics, market information and climatic conditions are generally the main factors driving rice farmers' decisions to adopt climate-resilient technologies, both individually and jointly. Follow-up policy interventions should focus on improving CI systems and promoting the joint adoption of climate-resilient technologies to improve rice farmers' well-being and enhance their resilience capacity to cope with incoming climatic uncertainty.     

The literature on the economic causes of and policy responses to obesity

This paper discusses economic perspectives on obesity, summarizes the economic literature and outlines potential policy responses. The paper provides the most up-to-date review of the literature. The literature illustrates the potential role of informational market failures and the dichotomy between the private and social costs of obesity. Market failures can act to provide a rationale for government intervention. Suggested factors for explaining the increase in the prevalence of obesity are discussed as relating to imperfect information, lifestyle changes and technology changes. Some of the potential remedial policies that are being debated in the literature include applying Pigouvian taxes, labelling regulation and advertising limitations.     

Quantifying the impact of farmers' social networks on the effectiveness of climate change mitigation policies in agriculture

To reduce agricultural greenhouse gas (GHG) emissions, farmers need to change current farming practices. However, farmers' climate change mitigation behaviour and particularly the role of social and individual characteristics remains poorly understood. Using an agent-based modelling approach, we investigate how knowledge exchange within farmers' social networks affects the adoption of mitigation measures and the effectiveness of a payment per ton of GHG emissions abated. Our simulations are based on census, survey and interview data for 49 Swiss dairy and cattle farms to simulate the effect of social networks on overall GHG reduction and marginal abatement costs. We find that considering social networks increases overall reduction of GHG emissions by 45% at a given payment of 120 Swiss Francs (CHF) per ton of reduced GHG emissions. The per ton payment would have to increase by 380 CHF (i.e., 500 CHF/tCO₂eq) to reach the same overall GHG reduction level without any social network effects. Moreover, marginal abatement costs for emissions are lower when farmers exchange relevant knowledge through social networks. The effectiveness of policy incentives aiming at agricultural climate change mitigation can hence be improved by simultaneously supporting knowledge exchange and opportunities of social learning in farming communities.     

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.     

The role of social networks in the adoption of competing new technologies in Ghana

We use a detailed dataset to examine the impact of social networks, conditional on contextual and individual confounders, on farmers' adoption of competing improved soybean varieties in Ghana. Based on the contagion conceptual framework, we employ a spatial autoregressive multinomial probit model to examine how neighbours' varietal and cross-varietal adoption of improved varieties affect a farmer's adoption decision in the social network. Our results show that adoption decisions in a network tend to converge on one variety, such that beyond a threshold of adopting neighbours of that improved variety, the cross-varietal effects tend to lose significance in the network. If the shares of adopting neighbours of the improved varieties are equal, we find evidence that farmers are not more likely to adopt either improved variety compared to farmers with no neighbours who have adopted the improved varieties. The findings demonstrate the significance of neighbourhood effects in the adoption of competing technologies.     

Household nutrition and income impacts of using dairy technologies in mixed crop–livestock production systems

Technologies like improved breeds of dairy cows and improved forages have the potential to significantly increase dairy cow productivity and farmers’ profits in developing countries. However, adoption of such technologies has been low in Ethiopia, despite numerous efforts to disseminate the technologies in the past. Some studies argue that adoption of technologies is low because welfare effects of the technologies could be insignificant or negative to certain groups of farmers. This article employed propensity score matching and inverse probability weighting estimator with regression adjustment to examine the difference in household nutrition and income between adopters and nonadopters of dairy technologies in rural Ethiopia. We find that adoption of cross‐bred dairy cows and improved forages increases household nutrition and income. The significant household nutrition and income impact for adopters support the notion that many Ethiopian smallholders have not adopted dairy technologies because adopters and nonadopters of dairy technologies have inherent differences in welfare outcome potentials. The results suggest that interventions that enhance access to farm resources and address barriers to input and output value chains could improve adoption of dairy technologies.     

Using Spatial Analysis to Study the Values of Variable Rate Technology and Information

For adoption of variable rate technology to increase, more knowledge of how crop yields respond to inputs is needed. As the necessary agronomic research involves approximating site‐specific yield response functions, data used inherently lend themselves to spatial analysis. We discuss the different types of spatial analyses that may be appropriate. Then we present a taxonomy for the discussion of the economics of technology and information, and use it to review studies that have contributed significantly to the literature over the past few years. We contend that longer‐term, multilocation agronomic experiments are needed for the estimation of site‐specific ex ante optimal variable input rates, and of expected profitability of variable rate technology and information.