Impact of Genetically Engineered Varieties on the Cost Structure of Corn and Soybean Production in Canada

This paper investigates the impact of genetically engineered (GE) varieties on the cost structure of corn and soybean production in Canada. Employing an adoption index for each farm and a time trend with farm‐level data on production costs of grain corn and soybeans from 2000 to 2007, a translog cost function and the associated input‐share equations are estimated. The use of the adoption index improves the estimates of technological change and multifactor productivity (MFP) growth. The results demonstrate that the adoption of GE corn and soybean reduced the variable costs of production by 0.62% per year. The MFP of corn and soybean grew by 2.0% per year during the study period, and 31% of this growth is attributable to GE varieties of these crops. The results also reveal that the adoption of GE varieties reduced the cost shares of fertilizer, herbicides and pesticides, and machinery in corn and soybean production. While the adoption of GE varieties increased the cost shares of seeds and custom works including labor, only the former was statistically significant.     

Environmental Stewardship and Technical Efficiency in Canadian Prairie Canola Production

This study examines beneficial management practice (BMP) adoption and technical efficiency for canola producers in the Canadian Prairie Provinces. A Just‐Pope stochastic frontier production function is estimated using data from a survey of canola producers. Yield is modeled as a function of nutrients and precipitation. A linear inefficiency function includes farm specific variables and a set of binary variables representing BMP adoption. BMP variables for nutrient management planning and precision farming are positively related to technical efficiency while results for the other BMP indicators are mixed. Model estimates appear to be significantly influenced by moisture problems that occurred through the Prairie region during the 2011 cropping year. The study results suggest that for Western Canadian canola producers, there is potential complementarity for some BMPs in terms of improving technical efficiency while simultaneously advancing environmental stewardship.     

The impact of soil conservation and output diversification on farm income in Central American hillside farming

This article analyzes the determinants of farm income among hillside farmers participating in natural resource management projects in El Salvador and Honduras. The farm income function was evaluated using a system of equations in which income is determined simultaneously by the farmer's decision to adopt soil conservation technologies and by the level of diversification (number of agricultural activities) on the farm. The database used comes from surveys administered to 678 beneficiaries of these projects during 2002. The econometric results suggest that all the variables related directly to land use (i.e., output diversification, soil conservation practices and structures, and the adoption of forestry systems) have a positive and statistically significant association with farm income. Also, farmers who own land enjoy higher farm incomes than those who do not. The results indicate that when investing in natural resource management projects, governments and multilateral development agencies should pay close attention to output diversification, land tenure, and human capital formation as effective instruments in increasing farm income.     

The Adoption of Genetically Modified Cotton and Poverty Reduction in Pakistan

This article employs a propensity score‐matching approach to examine the direct effects of adoption of Bacillus thuringiensis (Bt) cotton on yields, pesticide demand, household income and poverty, using cross‐sectional data from a survey of farmers in the Punjab province of Pakistan. Generally, the findings reveal that adoption of the new technology exerts a positive and significant impact on cotton yields, household income and poverty reduction, and a negative effect on the use of pesticides. The positive and significant impact of the technology on yields and household income is consistent with the potential role of new agricultural technology in directly reducing rural poverty through increased farm household income.     

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.     

Adoption of New Technologies in Ethiopian Agriculture: The Case of Tegulet-Bulga District,Shoa Province

Adoption of agricultural production technologies in developing countries is influenced by a wide range of economic and social factors as well as physical and technical aspects of farming and the risk attitude of farmers. It is important to understand the role of these factors to ensure the development of appropriate technologies and the design of successful development projects. This study examines the impact of such factors on the adoption of single-ox, fertilizer and pesticide technologies as part of a post-drought recovery project in Tegulet-Bulga district in Ethiopia. Models to evaluate the probability of adoption are specified for the respective technologies and are estimated using a logit maximum likelihood procedure, results indicate that the most significant variable affecting the probability of adoption of all three technologies is farm size; the impact is negative for single-ox technology and positive for fertilizer and pesticide use. Economic factors such as income, wealth and debt generally exhibit statistically significant influence on the adoption of single-ox and pesticide technologies as do family size, access to outside information, education and experience. The effect of socio-economic factors on adoption of fertilizer and pesticide technologies is greater in the area which has more access to outside information and off-farm activities (Ankober) than in more ‘self-contained’ area (Seladengay). The impact of the degree of risk aversion of farmers is found to be significant and negative for single-ox technology in both areas, and for fertilizer and pesticide technologies in only one area. The predicted probabilities of technology adoption by an average farmer are found to increase dramatically with the level of education and access or exposure to outside information.     

Exploring agricultural advice networks,beneficial management practices and water quality on the landscape: A geospatial social-ecological systems analysis

Agricultural practices have been linked to detrimental effects on ecosystems, with water quality of particular concern. Research has been devoted to understanding uptake of beneficial, or best, management practices (BMPs) in agriculture; however, sources of advice and subsequent effects on the landscape have not been elucidated. This study set out to understand (1) what sources of information agricultural producers rely on when making land-management decisions; (2) the characteristics of their advice networks; and (3) how the advice network linked spatially to water quality on the landscape. A watershed in Alberta was used as a case study and respondents identified that regional advisors were relied upon most often for advice and these advisors had the most influence on the adoption of BMPs. Results indicate that respondents with connections to regional actors implemented more BMPs that those without. Regional government actors had a greater effect than regional non-governmental actors. Local actors played a lesser role in advice networks related to BMP adoption. A 3D geovisualization was used to explore linkages among advisors, BMPs, and water quality. This technique may be useful for other scenarios and can contribute to policy development and enhanced practices.     

资本禀赋、生态认知与农户水土保持技术采用行为研究——基于生态补偿政策的调节效应

本文基于黄土高原地区陕西、甘肃和宁夏3省份1152户农户调查数据,构建资本禀赋、生态认知、生态补偿政策和农户水土保持技术采用行为的理论模型,运用Heckman样本选择模型进行实证分析,揭示资本禀赋、生态认知、生态补偿政策对农户水土保持技术采用行为的影响机理。研究结果表明:(1)资本禀赋中,农用机械数量、林地面积对农户水土保持技术采用及采用程度都具有显著的正向影响,耕地面积对采用程度有显著的正向作用,总收入对采用行为有显著的负向作用,相互信任对采用行为有显著的正向作用;(2)农户生态认知对其水土保持技术采用行为具有显著的正向作用;(3)生态补偿政策对农户采用水土保持技术具有显著的正向作用,并且对资本禀赋、生态认知与水土保持技术采用及采用程度关系中具有正向调节效应。     

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

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

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.     

Modern rice technology and regional wage differentials in the Philippines

Fear has been widely expressed that the modern rice varieties have created large disparities in regional income distribution, as the productivity gap between favorable and unfavorable rice-production environments widened due to differential technology adoption throughout South and Southeast Asia over the last two decades. Technology affects the income of farm population directly through its effects on productivity and factor use, and indirectly through its effect on factor prices. In particular, the ultimate distributional impact of modern varieties will critically depend on the interregional labor-market adjustments through migration in response to regional wage differentials created by the differential technology adoption, since labor is the main resource of the majority of the rural population. We studied favorable and unfavorable rice-growing villages in the Philippines, and found that adoption of modern varieties during the 1970s was positively related to population growth rate. Contrary to popular belief, no association was observed between wage rates and adoption of modern varieties as of 1986. These findings support the hypothesis that the differential adoption of modern rice varieties induced interregional labor migration toward equalization of wage income across different production environments.     

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.     

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.     

Adoption and impacts of sustainable intensification practices in Ghana

Sustainable agricultural intensification requires the use of multiple agricultural technologies in an integrated manner to enhance productivity while conserving the natural resource base. This study analyses the adoption and impacts of sustainable intensification practices (SIPs) using a dataset from Ghana. A multivariate probit (MVP) model was estimated to assess the adoption of multiple SIPs. Moreover, we used a multivalued semi-parametric treatment effect (MVTE) model to estimate the effects of adopting multiple SIPs on maize productivity. The MVP model results show, among others, that access to market, capital, and information/knowledge would enhance the adoption of SIPs. The MVTE model results show that a higher number of SIPs is associated with higher productivity which is more visible when commercial inputs are used in combination with cultural practices. These results have the following policy implications. First, they imply that good rural infrastructure and agricultural services such as rural road network, village-level input delivery system, input credit, and multiple information/knowledge sharing approach (instead of the conventional singular formal information/knowledge sharing approach) can enhance adoption. Second, the results suggest that promoting an integrated use of technologies, instead of a single technology, would have a positive impact on farm productivity and farm household income.     

The economic impact of bean disease resistance research in Honduras

This paper presents evidence of recent adoption rates of disease resistant bean varieties (RVs), the farm‐level benefits of RV adoption, and the ex post rate of return to disease resistant bean research in Honduras. Results from a farm‐level survey in 2001 in the two principal bean‐producing regions of the country show that 41–46% of bean farmers (depending upon the season) have adopted an RV, and that adoption is neutral with respect to farm‐size and market orientation. An expected utility framework was used to estimate the farm‐level benefits of RV adoption, using a combination of experimental trial and farm‐level survey data. Adopters gain the equivalent of 7–16% (depending on the variety) in bean income from the yield loss averted through RV use. The ex post rate of return to disease resistant bean research in Honduras from 1984 to 2010 is 41.2%.     

Modern Rice Technologies and Productivity in the Philippines: Disentangling Technology from Managerial Gaps

Using cross‐sectional farm‐level data from 3,164 rice‐farming households in the Philippines, we measure the impact of modern rice technologies on farm productivity while disentangling technology gaps (the distance between production frontiers) from managerial gaps (differences in technical efficiency). To do so, we combine a recently developed stochastic production frontier framework with impact evaluation techniques to control for biases stemming from observables and unobservables. First, we find an adequate control group using propensity score matching to mitigate the effect of biases from observable variables. Then, we test for biases that might arise from unobserved variables using a stochastic frontier framework corrected for self‐selection. Finally, we estimate meta‐frontiers to assess productivity differences between adopters and non‐adopters. The analysis shows that the adoption of certified seeds has a significant and positive impact on productivity, efficiency and net income in rice farming.     

Unconventional adjustment strategies for rural households in the less developed areas in Greece

International competition in agricultural production is intensifying following the implementation of the 1993 accord of the General Agreement on Tariffs and Trade. The production of conventional farm products in surplus is being discouraged by means of indirect economic disincentives. The Common Agricultural Policy has already adjusted to unprotected national markets within the European Union and greater market orientation is being achieved mainly through price reductions. Farmers in the less developed areas in Greece, where agricultural activity is still the main source of income and employment, have been responding to policy reforms by seeking part-time employment and income in non-farm enterprises. The adoption of alternative, unconventional farm enterprises that use farm resources in an innovative and quantitatively different way does have the potential for bringing in a new source of income to farm business. For the purpose of this research three adjustment strategies were recognised. The ‘conventional’ (no change) pathway is based on traditional, region-specific products, production methods and services. The adoption of the ‘new crop’ pathway refers to the redeployment of resources into new agricultural products, whereas farms on the market integration Pathway redeploy resources into new marketing services and agricultural product processing on the farm. The new crop and the market integration pathways are identified as unconventional adjustment strategies. Results derived from multinomial logit analysis highlight the major constraints and opportunities associated with the adoption of new crops and market integration practices. Farmers who have adopted unconventional practices are influenced by factors external to the farm. such as contacts with institutions, and have a high probability of having higher debts. These farmers are likely to depend heavily on seasonal labour and rented land. The fact that market integration activities are associated with smaller farms in conjunction with off-farm work signifies the importance of establishing an integrated rural development policy approach. Public policy involvement in enhancing dissemination of information concerning unconventional enterprises is emphasised.     

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.     

Nonfarm employment,agricultural intensification,and productivity change: empirical findings from Uganda

This article uses panel data from the Living Standards Measurement Study‐Integrated Surveys on Agriculture for Uganda to assess the farm‐level effects of nonfarm employment on agricultural intensification and productivity change. A sample selection model is used to account for both unobserved heterogeneity and potential simultaneity between agricultural production and nonfarm income. Results show that nonfarm employment can have differential impacts on farm technology intensity and productivity. Nonfarm income is found to have a positive impact on farm hired labor and improved seed intensity; a negative effect on on‐farm family labor use; and no significant impact on fertilizer, soil water management, and joint use of farm technologies. The econometric evidence also indicates that agricultural productivity declines as nonfarm income increases. Taken together, our findings reveal important trade‐offs between nonfarm employment and income and farm productivity growth under smallholder agriculture. The results indicated that targeted policies are required to reduce these potential trade‐offs between nonfarm employment and agricultural intensification and productivity change.     

Economic impacts of smallholder farmers’ adoption of drought-tolerant maize varieties

Drought and high temperatures are major threats to sustainable food production and consequently the livelihoods of the majority of Africans who depend on fragile agricultural systems. As a response to these threats, climate-smart agricultural technologies, such as drought-tolerant maize (DTM) varieties, have been developed and promoted on the continent. It is well-known that the adoption of improved technologies generally impacts positively on the wellbeing of adopters. Nevertheless, the magnitude of the impact of any technology or intervention is always an empirical question. Therefore, this study sought to determine the factors that influence the adoption of DTM and subsequently estimate how yield, commercialization intensity, and farm income are affected by adoption. To establish causation, we relied on observations from 200 farm households in the Northern Region of Ghana and estimated an instrumental variable regression. Consistent with findings reported in the literature, we found that DTM adoption is primarily driven by access to seed, extension service, labor availability, and location of farm households. In addition, we found that DTM adoption positively impacts on yield and commercialization intensity. The magnitude of impact is not trivial. For example, the yield of farm households increased by more than 150% (936 kg/ha) following DTM adoption. These results imply that policy-makers and development practitioners must support research and promotion of climate-smart agriculture to improve adoption and welfare indicators, such as yield and commercialization.