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.     

Adoption of improved chickpea varieties: KRIBHCO experience in tribal region of Gujarat, India

The study aims to track adoption of improved chickpea varieties, and assess their on‐farm benefits in some remote and backward tribal villages in Gujarat, India, where few newly developed varieties were introduced by a non‐government organization. It also determines key factors which were influencing their adoption. The study found that adoption of improved chickpea varieties was gradually increasing by replacing a prominent local variety. Duration of crop maturity, farm size, yield risk, and farmers' experience of growing chickpea crop were significantly influencing their adoption. The on‐farm benefits as a result of improved varieties were realized in terms of increased yield levels, higher income and labor productivity, more marketable surplus, price premium and stabilized yields in fluctuating weather. Breeding short duration varieties with stable yield levels under varying weather, and organizing seed multiplication and dissemination in regions, where moisture stress is a problem during maturity of chickpea, are the major suggestions.     

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.     

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.     

Effect of modern rice varieties and irrigation on household income distribution in Nepalese villages

Since high-yielding modern rice varieties (MVs) are adopted only in favorable production environments, significant regional productivity differentials have emerged in Nepal. This study explores the distributional consequences of such differential MV adoption based on an intensive survey of favorable and unfavorable villages. We found that MV adoption increased returns to land but decreased family labor earnings from rice production, as it facilitated the substitution of hired for family labor. As a result, the differential MV adoption did not significantly worsen the household income distribution according to the results of the counterfactual Gini decomposition analysis.     

Productivity and Land Enhancing Technologies in Northern Ethiopia: Health, Public Investments, and Sequential Adoption

The adoption of more efficient farming practices and technologies that enhance agricultural productivity and improve environmental sustainability is instrumental for achieving economic growth, food security, and poverty alleviation in sub-Saharan Africa. Our research examines the interaction between public investments, community health, and adoption of productivity and land enhancing technologies by households in the northern Ethiopian state of Tigray. Agricultural technology adoption decisions are modeled as a sequential process where the timing of choices can matter. We find that time spent sick and opportunity costs of caring for sick family members are significant factors in adoption. Sickness, through its impact on household income and labor allocation decisions for healthcare and other activities, significantly reduces the likelihood of technology adoption. Our findings suggest that agencies working to improve agricultural productivity and land resource conservation should consider not only the financial status of potential adopters, but also their related health situation.     

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.     

农机社会化服务对农业劳动生产率的影响研究

[目的]农业劳动生产率的提高是中国农业现代化的重要特征,进一步探讨农机社会化服务对农业劳动生产率的作用效果具有现实意义。[方法]文章基于2019年全国13省份玉米种植户调查数据,采用OLS回归模型与倾向得分匹配法,分析了农机社会化服务对农业劳动生产率的影响效应,探讨影响效应在不同地形条件、兼业程度的组群差异,并考察了不同环节农机社会化服务对农业劳动生产率的影响差异。[结果]（1）农机社会化服务正向显著影响农业劳动生产率,采纳农机社会化服务会促使农户农业劳动生产率显著提高18.8%。但农户采纳农机社会化服务的作用效果具有环节异质性。采纳耕整地、播种、灌溉排水和收获环节农机社会化服务会促使农户农业劳动生产率分别显著提高21.2%、17.4%、22.9%和18.3%;(2)而农户采纳植保环节农机社会化服务对农业劳动生产率并不具有显著影响。农户采纳农机社会化服务对劳动生产率的影响效应还存在禀赋差异,平地农户采纳农机社会化服务使其农业劳动生产率显著提高21.9%,而坡地山地农户采纳农机社会化服务对农业劳动生产率没有表现出显著的影响。（3）纯农业户与兼业农户采纳农机社会化服务都会对农业劳动生产率产...     

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.     

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.     

Productivity growth and convergence in crop, ruminant, and nonruminant production: measurement and forecasts

Projections of future productivity growth rates in agriculture are an essential input for a great variety of tasks, ranging from development of an outlook for global commodity markets to the analysis of interactions between land use, deforestation, and ecological diversity. Yet solid projections for these variables have proven elusive—particularly on a global basis. This is due, in no small part, to the difficulty of measuring historical total factor productivity growth. Consequently, most productivity projections are based on partial factor productivity measures that can be quite misleading. The purpose of this work is to provide worldwide forecasts of agricultural productivity growth till the year 2040 based on the latest time series evidence on total factor productivity growth for crops, ruminants, and nonruminant livestock. The results suggest that most regions in the sample are likely to experience larger productivity gains in livestock than in crops. Within livestock, the nonruminant sector is expected to continue to be more dynamic than the ruminant sector. Given the rapid rates of productivity growth observed recently, nonruminant and crop productivity in developing countries may be converging to the productivity levels of developed countries. For ruminants, the results show that productivity levels in developing countries are likely to be diverging from those in developed countries.     

Impact of hybrid rice on input demand and productivity

This paper uses farm-level data collected from a sample of 500 households in Hunan province, China, to analyze the impact of hybrid rice on input demand and productivity. Based on regression analyses, it is found that, compared with conventional modern varieties, hybrid rice uses about 4% less labor inputs, 2% less draft animal services, and 6% more chemical fertilizers. The lesser requirements for labor and draft animal services probably arise from hybrid rice's lower seeding rate. Due to heterosis and high seed costs, the use of F₁ seed is economized to about one-third to one-fourth that of conventional varieties. Therefore, less labor and animal power is needed for seed-bed preparation and transplanting. It is also found that, given the same level of inputs, the yield advantage of hybrid rice over the conventional modern varieties is about 19%. Because of the productivity potential, hybrid rice is a candidate for the second-generation “Green Revolution” in other parts of Asia.     

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.     

Enhancing productivity on suburban dairy farms in China

Dairy farms in China's suburban areas have been playing an important role in providing urban markets with fresh milk. With the rising demand for fluid milk and dairy products in the cities, there is a perception that small and scattered dairy farms in China's provinces are gradually disappearing and more concentrated dairy cattle farming is being formed near suburban areas. This article uses farm‐level survey data and stochastic input distance functions to make estimates of total factor productivity (TFP) on suburban dairy farms, as well as for the entire dairy sector. The results show that over the past decade TFP growth has been positive on suburban dairy farms, and this rise in productivity has been driven mostly by technological change. However, at the same time we find that, on average, the same farms have been falling behind the advancing technical frontier. We also find one of the drivers of the suburban dairy sector is the relatively robust rate of technological change of these farms, which has been more rapid than on farms in the dairy sector as a whole. The results suggest that efforts to achieve greater adoption of new technologies and better advice on how to use the technologies and manage production and marketing within the suburban dairy sector will further advance productivity growth in the sector.     

GM crop technology and trade restraints: economic implications for Australia and New Zealand*

How much might the potential economic benefit from enhanced farm productivity associated with crop biotechnology adoption by Australia and New Zealand (ANZ) be offset by a loss of market access abroad for crops that may contain genetically modified (GM) organisms? This paper uses the Global Trade Analysis Project (GTAP) model to estimate effects of other countries' GM policies without and with ANZ farmers adopting GM varieties of various grains and oilseeds. The gross economic benefits to ANZ from adopting GM crops under a variety of scenarios could be positive even if the strict controls on imports from GM‐adopting countries by the European Union are maintained, but not if North‐East Asia also applied such trade restaints. From those gross economic effects would need to be subtracted society's evaluation of any new food safety concerns and negative environmental externalities (net of any new environmental and occupational health benefits), as well as any extra costs of segregation, identity preservation and consumer search.     

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.     

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.     

Resource saving and productivity enhancing impacts of crop management innovation packages in Ethiopia

Crop management innovations are often not discrete fixed stand‐alone options—and their adoption may imply various combinations and adaptations. This potentially confounds their impact assessment. This article assesses the resource saving and productivity enhancing impacts of a crop management package revolving around minimum tillage in maize‐based farming systems in northwest Ethiopia. An endogenous switching regression model was applied to plot‐ and household‐level survey data collected from 290 rural households operating 590 maize plots during the 2012 production year. Controlling for variations in plot and household characteristics, the average effect of minimum tillage package (minimum tillage package) on maize productivity is 0.44 t/ha. Compared to conventional practice (CP), adoption of the MTP decreased the average male and female labor use in maize production by 14.4 and 8.2 person‐days per ha, respectively. Similarly, MTP adoption decreased draft power use for land preparation by 13.2 pair of oxen‐days per ha. Compared to CP, in general, there is a considerable short‐run maize productivity gain and reduction in labor and draft power use under MTP.     

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 impact of integrated livestock disease management for food security in Togo

In sub-Saharan Africa, livestock is one of the key channels through which most households meet their food security needs. However, diseases such as the African Animal Trypanosomosis (AAT) constrain productivity. Using data from 445 randomly sampled small-scale cattle farmers, this paper investigates the role of integrated livestock disease control on household food security. Using a novel approach to link different food security measures to cattle productivity, the paper identifies the channels of impact at the household level. Methodologically, the paper estimated the propensity score matching algorithm to net out the effect of adoption. The results show that households who adopt RDU have record livestock productivity and higher consumption per capita expenditures. They tend to be more food secure, experience lower seasonal food supply fluctuations and experience a lower probability of falling below the food poverty line.