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.     

Assessing the effectiveness of rural credit policy on the adoption of integrated crop-livestock systems in Brazil

This study analyzes the effectiveness of rural credit policy to increase the adoption of ICLS. Analyzes are based on a survey with 175 farmers in the State of São Paulo, Brazil. Our estimates suggest that rural credit has positive and relevant impacts on the adoption of ICLS. In turn, the adoption of these systems may also involve investments in fixed capital and increases in operational costs, which create additional demand for rural credit. Other factors, such as access to extension policy, production scale, ex-ante perceptions, and market infrastructure also explain ICLS adoption. The access to rural credit policy is also determined by dependence on farm income, farmer’s perception of transaction costs, and supply of credit in the municipality. The study finally discusses important implications for the devising of rural credit policies and the diffusion of sustainable production systems in developing countries.     

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.     

The determinants of technology adoption by UK farmers using Bayesian model averaging: the cases of organic production and computer usage

We review and implement a reversible jump approach to Bayesian model averaging for the Probit model with uncertain regressors. Two applications are investigated. The first is the adoption of organic systems in UK farming, and the second is the influence of farm and farmer characteristics on the use of a computer on the farm. While there is a correspondence between the conclusions we would obtain with and without model averaging results, we find important differences, particularly in smaller samples. Concerning the adoption of an organic system, we find that attitudes to the sustainability of the current system along with the ability of organic farms alone to satisfy society’s needs for food are influential. Additionally, the source of management information used by the farmer has a significant impact. Regarding the adoption of computers, we confirm the findings of previous work that the level of education affects uptake and that age is a factor determining adoption. We also find that dairy and organic farms are more likely to use a computer. The physical size of the farm is positively associated with the probability of computer use while net farm income has a limited impact.     

Sequential Adoption of Site-Specific Technologies and Its Implications for Nitrogen Productivity: A Double Selectivity Model

This paper analyzes the sequential decision to adopt two site-specific technologies, soil testing and variable rate technology, and the impact of adoption on nitrogen productivity. The results indicate that while farm location was a key variable influencing adoption of soil testing, farm size, human capital, and innovativeness of farmers had a significant impact on adoption of variable rate technology in four Midwestern states. A double selectivity model applied to correct for sample selection bias shows that adoption leads to significant gains in nitrogen productivity for farms with below average soil quality but statistically insignificant gains for farms with above average soil quality.     

Determinants of herbicide use in rice production in the Philippines

This study identifies farm‐specific and market factors affecting the adoption of herbicides and the level of herbicide use by rice farmers in the Philippines. This requires the application of a modified version of Heckman's two‐step method to estimate a random‐effects double‐hurdle model for unbalanced panel data. The age of the farmer, household size, and irrigation use are significant determinants of the decision of farmers to adopt herbicides as an alternative to manual weeding, while economic variables such as the price of herbicides, total income, and access to credit determine the level of herbicide use. Determinants of both adoption and level are land ownership, farm area, and the method of crop establishment. These results are potentially relevant when designing policies to reduce excessive herbicide use or to encourage the adoption of alternative weed control methods such as integrated weed management.     

Integrating Technology Traits and Producer Heterogeneity: A Mixed-Multinomial Model of Genetically Modified Corn Adoption

This article proposes a model of technology adoption that integrates demand for individual traits of new technologies with the potential for heterogeneity based on farm and farmer characteristics. The model is applied to recent genetically modified corn adoption data from Minnesota and Wisconsin farmers, using a mixed-multinomial logit (MMNL) model to estimate the effects of traits and farm and farmer characteristics on adoption outcomes. This approach allows explicit recovery of estimates of farmers' shadow prices for individual technology traits. Results show the importance of producer and regional heterogeneity in preferences for seed traits.     

Group heterogeneity and the economic effect of farmer organisation participation: Empirical evidence from Taiwan

We explore the effects of different farmer organisations on smallholder farmers' economic performance. The average treatment effect of switching between different farmer organisations is examined. In addition, based on the premise that a higher level of social capital is accumulated through participation in multiple farmer organisations, we also investigate how the economic consequences of farmer organisation membership vary with the intensity of participation. Our conceptual model explicitly includes social capital to provide a micro-foundation and a theoretical justification for the linkage between farmer organisation participation and the economic outcome. This indicates that participating in different types of farmer organisations is beneficial for farm households only when the returns from social capital investment outweigh the time cost of participation. Our empirical results suggest that membership of farmer organisations that are more homogeneous in terms of member specialty and similarity in production and marketing activities results in a significant increase in farm sales revenue and net returns. This result supports the view that technological proximity accentuates knowledge spillovers within the farmer organisations, and thus leads to better economic outcomes. In line with the prediction of the theoretical model, the average treatment effect of participation is found to increase with the number of organisations that farmers belong to. Moreover, results from the quantile regression provide empirical evidence supporting increasing returns to social capital accumulated through participation in several farmer organisations.     

Extension services,product quality and yields: the case of grapes in Argentina

This article studies the impact of publicly subsidized agricultural extension services on yields and product quality. We use panel data from grape producers in Mendoza, Argentina to estimate the impacts of farmer trainings. We find a negative overall impact on yields and evidence of a positive average impact on the adoption of higher‐quality grape varieties. By analyzing the dynamic pattern of the estimated effects, we find evidence of a temporary decrease in yields suggesting the existence of an adjustment process following the introduction of higher‐quality grapes. The overall negative effect on yield is driven by a sharp drop in the year of participation. This fades after year one, and two to three years after treatment we observe increases in higher‐quality grape production. Findings reinforce the importance of temporal dimension of extension services.     

Measuring Farm and Market Level Economic Impacts of Improved Maize Production Technologies in Ethiopia: Evidence from Panel Data

While it is often recognised that agricultural technology adoption decisions are intertwined and best characterised by multivariate models, typical approaches to examining adoption and impacts of agricultural technology have focused on single technology adoption choice and ignored interdependence among technologies. We examine farm‐ and market‐level impacts of multiple technology adoption choices using comprehensive household survey data collected in 2010/11 and 2012/13 in Ethiopia. Economic surplus analysis combined with panel data switching endogenous regression models are used to compute the supply shift parameter (K‐shift parameter), while at the same time controlling for the endogeneity inherent in agricultural technology adoption among farmers. We find that our improved technology set choices have significant impacts on farm‐level maize yield and maize production costs, where the greatest effect appears to be generated when various technologies are combined. The change in maize yield and production costs results in an average 26.4% cost reduction per kilogram of maize output (the K‐shift parameter). This increases the producer and consumer surpluses by US$ 140 and US$ 105 million per annum, respectively. These changes in economic surplus help to reduce the number of poor people by an estimated 788 thousand per year. We conclude that deliberate extension efforts and other policies that encourage integration of technologies are important for maize technologies to yield their full potential at both farm and market levels.     

Achieving successful farmer engagement on greenhouse gas emission mitigation

This paper explores the potential for farmers’ engagement on the issues related to greenhouse gas (GHG) emission mitigation in extensive low-input livestock farming systems. The framework used was based on Participatory Action Research. This involved integrating quantitative evidence on GHG emission impacts at the farm level and qualitative data on the obstacles to the adoption of innovation based on farmers’ perceptions and attitudes to climate change. The study aims at building social capital among 14 farmers in the South West and West Midlands regions in England, and it evaluates the potential for the adoption of emission mitigation strategies. The Rapid Farm Practices Appraisal (RFPA) tool was created to assess farm practices based on their mitigation potential. Practices were assessed twice over 6–9 months. Semi-structured interviews were used to assess barriers and opportunities to farmer engagement and on-farm innovation. Farmers were invited to a focus group meeting to network with other farmers and engage with researchers. All farmers participated in the 2 farm assessments, but only half the farmers adopted changes in farm management. All farmers appreciated the RFPA tool, the clearness of the information provided and the focus of the tool on practices directly. The main obstacles to innovation were limited financial capital, lack of trust in government action and confusion over the effectiveness of farm advice on mitigation. The lack of long-term flexibility of agricultural policies and the source of information greatly influenced the acceptance of advice. Results suggest the potential for the expansion of the RFPA tool to include economic assessment of farm practices and the engagement of a larger pool of farmers and farming systems. The tool could be used to support the GHG Action Plan and future environmental policies, and as an integrated self-assessment tool for farmers under Environmental Stewardship Schemes.     

Adoption of climate‐smart practices and its impact on farm performance and risk exposure among smallholder farmers in Ghana

Increased climate variability during the last four decades has made the agricultural environment in many developing countries more uncertain, resulting in increasing exposure to risk when producing crops. In this study, we use recent farm‐level data from Ghana to examine the drivers of individual and joint adoption of crop choice and soil and water conservation practices, and how adoption of these practices impacts on farm performance (crop revenue) and exposure to risks (skewness of crop yield). We employ a multinomial endogenous switching regression model to account for selectivity bias due to both observable and unobservable factors. The empirical results reveal that farmers’ adoption of crop choice and soil and water conservation leads to higher crop revenues and reduced riskiness in crop production, with the largest impact on crop revenues coming from joint adoption. The findings also show that education of the household head, access to extension and weather information influence the likelihood of adopting these practices. Thus, enhancing extension services and access to climate information and irrigation can reduce gaps in adoption of soil and water conservation and crop choice, considered as climate‐smart practices that will eventually improve crop revenues and reduce farmers’ exposure to climate‐related production risks.     

Bias from Farmer Self‐Selection in Genetically Modified Crop Productivity Estimates: Evidence from Indian Data

In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm‐level yield gains from GM crop adoption. Yet most farm‐level studies in the literature do not control for farmer self‐selection, a potentially important source of bias in such estimates. We use farm‐level panel data from Indian cotton farmers to investigate the yield effect of GM insect‐resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self‐selection. A production function is estimated using a fixed‐effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross‐sectional estimates of the yield effect of Bt cotton, which do not control for self‐selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.     

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.     

Understanding the adoption of a portfolio of sustainable intensification practices in eastern and southern Africa

This paper explores smallholder farmers’ adoption decisions of multiple sustainable intensification practices (SIPs) in eastern and southern Africa. We develop a multivariate probit model using plot-level data gathered from maize–legume farming systems in Ethiopia, Kenya, Malawi, and Tanzania. We find that some practices used in maize production are complementary while others are substitutable. The adoption of SIPs is influenced by social capital and networks, quality of extension services, reliance on government support during crop failure, incidence of pests and diseases, resource constraints, tenure security, education, and market access. The results provide insight into the further efforts needed to encourage greater adoption of SIPs.     

Apparent Gains,Hidden Costs: Examining Adoption Drivers,Yield, and Profitability Outcomes of Rotavator Tillage in Wheat Systems in Nepal

The ‘high speed’ rotavator is used for shallow tillage to create a fine tilth and incorporate crop residues, often with a single tractor pass. Rotavator tillage has spread quickly in many parts of South Asia, despite short-term experimental trials suggesting deteriorating soil quality and crop yield penalties. Evidence of rotavator impacts on farmer fields across soil gradients and time is largely absent. From a farm household survey conducted among wheat farmers in Nepal, we estimate wheat yield and profitability outcomes for rotavator adopters and non-adopters using propensity score matching. We find that rotavator adoption leads to inferior outcomes, despite significant cost savings for land preparation (US$ 11–15 per hectare). With rotavator adoption, farmers lose about 284–309 kg of wheat grain and about US$ 93–101 of profits on average per hectare per season, and these penalties increase with longer-term use of the technology. Adoption of rotavator appears to be driven by the cost and time savings for land preparation. Against this backdrop, new policy and extension efforts are required that discourage rotavator use and favour more sustainable tillage technologies.     

Impact of land fragmentation and resource ownership on productivity and efficiency: The case of rice producers in Bangladesh

The paper analyzes the impact of land fragmentation and ownership of resources on productivity and technical efficiency in rice production in Bangladesh using farm level survey data. Results reveal that land fragmentation has a significant detrimental effect on productivity and efficiency as expected. The elasticity estimates of land fragmentation reveal that a 1% increase in land fragmentation reduces rice output by 0.05% and efficiency by 0.03%. On the other hand, ownership of key resources (land, family labour, and draft animals) significantly increases efficiency. The mean elasticity estimates reveal that a 1% increase in family labour and owned draft animal improve technical efficiency by 0.04% and 0.03%, respectively. Also, a 1% increase in the adoption of modern technology improves efficiency by 0.04%. The mean technical efficiency in rice production is estimated at 0.91 indicating little scope to improve rice production per se using existing varieties. Policy implications include addressing structural causes of land fragmentation (e.g., law of inheritance and political economy of agrarian structure), building of physical capital (e.g., land and livestock resources), improvements in extension services and adoption of modern rice technology.     

Landcare and Livelihoods: The Promotion and Adoption of Conservation Farming Systems in the Philippine Uplands

Slow adoption of conservation farming systems in the Philippine uplands is a major problem. To address this, the landcare approach, based on community landcare groups, is being piloted in several locations. The results of a study to evaluate the impact of the Landcare Program in Barangay Ned in Southern Mindanao are presented. The sustainable rural livelihoods approach was used as a framework for the evaluation. The study focused on two impacts, the adoption of conservation practices and the formation and development of landcare groups, drawing on four data sources—project reports, key informants, a questionnaire survey, and case studies of landcare groups. The Ned Landcare Program has been associated with rapid adoption of conservation farming practices and the rapid formation of landcare groups linked in an association. The main effect of the Program was to enhance human capital through practical, farmer-led training and extension, enabling farmers to incorporate soil conservation and agroforestry technologies in their farming systems, with desirable outcomes for livelihood security and environmental sustainability. The social capital formed, especially through the landcare association, was crucial to these outcomes. Ongoing partnerships with adequately resourced facilitating agencies were required to maintain the Landcare Program in the long term.