How does gender affect the adoption of agricultural innovations?

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

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.     

Rotational grazing adoption in cattle production under a cost‐share agreement: does uncertainty have a role in conservation technology adoption?

Rotational grazing has been promoted as a best management practice with environmental benefits and associated higher revenue. Its adoption rate has been relatively low. This study investigates the role of uncertainty in the adoption of rotational grazing with a cost‐share by cattle producers. Mail survey results indicate that 63–71 per cent of cattle producers are uncertain about adoption with a government cost‐share. The study suggests that the possibility of uncertainty should be considered in cases where willingness‐to‐pay is elicited in the context of adoption of technology.     

Self‐protection from weather risk using improved maize varieties or off‐farm income and the propensity for insurance

We investigate how self‐protection from the adoption of Improved Maize Varieties (IMV) and off‐farm income affects risk premiums for smallholder maize producers in Uganda. To unbundle these effects, we specify the cost of risk to explicitly capture four risk components—mean, variance, skewness, and kurtosis. Using unique plot‐level panel data for Uganda, we estimate and test moments of a flexible production function based on an expanded form of the Johnson S_U family distribution and proceed to simulate the degree of responsiveness of risk premiums and welfare estimates to marginal changes in the share of land under IMV and off‐farm income. Scenarios of joint adoption of IMV accompanied with low and high application of inorganic fertilizer, and the effect of off‐farm income when there is high and low supply of farm labor are examined. Results show that the use of IMV and off‐farm income substantially reduces risk premiums and the individual effect is much higher under low fertilizer application and high supply of farm labor, respectively. Thus implying that self‐protection is likely to reduce the propensity for index insurance especially if its design fails to consider the reduction in downside risk.     

Market imperfections,access to information and technology adoption in Uganda: challenges of overcoming multiple constraints

Limited empirical evidence exists on how multiple binding constraints influence the adoption of improved technologies by smallholder farmers. This article uses the case of groundnut variety adoption in Uganda to investigate the role of information, seed supply, and credit constraints in conditioning technology uptake. New data from a household survey in seven groundnut growing districts (n = 945) indicate that 8% of farmers lack information on new varieties, while 18% and 6% of farmers, respectively, cannot adopt mainly due to seed supply and capital constraints. A tobit‐type specification that considers all nonadopters as being uninterested in the technology (i.e., corner solutions) would lead to inconsistent parameter estimates and incorrect conclusions in this context. We therefore estimate a modified multi‐hurdle specification of demand for new varieties, taking into account how information, seed supply, and capital constraints jointly determine adoption probability and intensity. The study reveals new empirical insights on why agricultural technology adoption in Africa has lagged behind: slow uptake is not mainly due to a lack of economic incentives, but rather a reflection of information, seed supply, and credit constraints that prevent farmers from translating their desired demand into adoption of modern varieties. Policy implications are discussed.     

Household Determinants of the Adoption of Improved Cassava Varieties using DNA Fingerprinting to Identify Varieties in Farmer Fields: A Case Study in Colombia

We examine factors affecting the adoption of improved cassava varieties of 217 households in the Cauca Department in southwest Colombia. Using DNA fingerprinting through Single Nucleotide Polymorphisms (SNPs), we identified different cultivars in farmers fields. We also used this information to remove possible bias in the adoption model that could have resulted from a misclassification of improved varieties (IVs). As a result, we found that farmers substantially overestimate their use of IVs and there are important differences in the determinants of adoption between farmer self‐identification and DNA fingerprinting. This finding implies that the incorporation of DNA fingerprinting in IV adoption studies is important to ensure the accuracy of future agricultural economic research and the relevance of subsequent policy recommendations.     

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.     

Location and uptake: integrated household and GIS analysis of technology adoption and land use, with application to smallholder dairy farms in Kenya

CIS‐derived measures of location and space have increasingly been used in models of land use and ecology. However, they have made few inroads into the literature on technology adoption in developing countries, which continues to rely mainly on survey‐derived information. Location, with all its dimensions of market access, demographics and agro‐climate, nevertheless remains key to understanding potential for technology use. The measures of location typically used in the adoption literature, such as locational dummy variables that proxy a range of locational factors, now appear relatively crude given the increased availability of more explicit GIs‐derived measures. This paper attempts to demonstrate the usefulness of integrating CIS‐measures into analysis of technology uptake, for better differentiating and understanding locational effects. A set of GIs‐derived measures of market access and agro‐climate are included in a standard household model of technology uptake, applied to smallholder dairy farms in Kenya, using a sample of 3330 geo‐referenced farm households. The three technologies examined are keeping of dairy cattle, planting of specialised fodder, and use of concentrate feed. Logit estimations are conducted that significantly differentiate effects of individual household characteristics from those related to location. The predicted values of the locational variables are then used to make spatial predictions of technology potential. Comparisons are made with estimations based only on survey data, which demonstrate that while overall explanatory power may not improve with CIS‐derived variables, the latter yield more practical interpretations, which is further demonstrated through predictions of technology uptake change with a shift in infrastructure policy. Although requiring large geo‐referenced data sets and high resolution GIS layers, the methodology demonstrates the potential to better unravel the multiple effects of location on farmer decisions on technology and land use.     

Crossbred cow adoption and its correlates: Countable adoption specification search in Sri Lanka's small holder dairy sector

Considerable specification choice confronts countable adoption investigations and there is need to measure, formally, the evidence in favor of competing formulations. This article presents alternative countable adoption specifications—hitherto neglected in the agricultural‐economics literature—and assesses formally their usefulness to practitioners. Reference to the left side of de Finetti's (1937) famous representation theorem motivates Bayesian unification of agricultural adoption studies and facilitates comparisons with conventional binary‐choice specifications. Such comparisons have not previously been considered. The various formulations and the specific techniques are highlighted in an application to crossbred cow adoption in Sri Lanka's small‐holder dairy sector.     

Differential livelihood impacts of oil palm expansion in Indonesia

In this article, the impacts of oil palm adoption on livelihoods of smallholder farm households are analyzed. The study builds on survey data from Sumatra, Indonesia. Treatment‐effects and endogenous switching regression models suggest that smallholder households benefit from oil palm adoption on average. Part of the benefit stems from the fact that oil palm requires less labor than rubber, the main alternative crop. This allows oil palm adopters to allocate more labor to off‐farm activities and/or to expand their farmland. For households with a low land‐to‐labor ratio, rubber is typically a more lucrative crop than oil palm. Depending on various social and institutional factors, households’ access to land, labor, and capital varies, contributing to impact heterogeneity. Welfare gains associated with oil palm are more pronounced among households that have formal land titles and access to additional land to expand their farm size during the process of adoption.     

Adoption and Abandonment of Organic Farming: An Empirical Investigation of the Irish Drystock Sector

There is a considerable literature about the adoption of organic farming. However, possible abandonment of organic farming has received scant attention. Thus, relatively little is known about the exit decisions of farmers. In addition, most studies are based on a static framework where it is not possible to account for changes in farmer decisions over time. This article attempts to fill this gap in the literature by investigating the determinants that affect both adoption and abandonment of organic drystock farming over time. The use of duration analysis allows for the consideration of cross‐sectional and time‐varying factors over the study period from 1981 to 2008. Using this dynamic econometric framework revealed a significant time effect on entry and exit decisions. Overall, the results highlight that where no attempt is made to account for exit decisions and time effects, important information about sustainable farmer decisions may not be taken into consideration.     

Factors influencing adoption of conservation tillage in Australian cropping regions*

The purpose of this research is to improve understanding of conservation tillage adoption decisions by identifying key biophysical and socio‐economic factors influencing no‐till adoption by grain growers across four Australian cropping regions. The study is based on interviews with 384 grain growers using a questionnaire aimed at eliciting perceptions relating to a range of possible long‐ and short‐term agronomic interactions associated with the relative economic advantage of shifting to a no‐tillage cropping system. Together with other farm and farmer‐specific variables, a dichotomous logistic regression analysis was used to identify opportunities for research and extension to facilitate more rapid adoption decisions. The broader systems approach to considering conservation tillage adoption identified important determinants of adoption not associated with soil conservation and erosion prevention benefits. Most growers recognised the erosion‐reducing benefits of no‐till but it was not an important factor in explaining whether a grower was an adopter or non‐adopter. Perceptions associated with shorter‐term crop production benefits under no‐till, such as the relative effectiveness of pre‐emergent herbicides and the ability to sow crops earlier on less rainfall were influential. Employment of a consultant and increased attendance of cropping extension activities were strongly associated with no‐till adoption, confirming the information and learning‐intensive nature of adopting no‐till cropping systems.     

Energy‐saving Technology Choices by Dutch Glasshouse Firms

This paper estimates a sequence of energy‐saving technology choices by Dutch glasshouse firms. The model allows for time‐constant, firm‐specific effects and serial correlation of errors and it is estimated on panel data over the period 1991–1995. The unobserved error sequences are simulated in the model in such a way that they are consistent with the observed choices. The results suggest that positive revenue shocks encourage adoption of new technologies. The choices also exhibit firm‐specific persistency over time. An increase of the price of energy encourages the adoption of a highly efficient energy‐saving technology. The probability of investing in energy‐saving technologies also decreases with capital invested in structures (e.g. double glazing of glasshouses) and increases with capital in energy installations.     

The impact of safety nets on technology adoption: a difference‐in‐differences analysis

This article contributes to a growing body of empirical literature relating credit constraints and incomplete insurance to investment decisions. We use panel data from rural Ethiopia to investigate whether participation in a safety net program enhances fertilizer adoption. Using a difference‐in‐differences estimator and inverse propensity score weighting, we find that participation in Ethiopia's food‐for‐work (FFW) program increased fertilizer adoption in the short run, but not in the long run. Results also indicate that the intensity of fertilizer usage increased with livestock holdings for FFW‐participant households, providing some evidence that the intervention helped asset‐rich farm households more than asset‐poor households. We find no significant effects of free distribution on fertilizer adoption or intensification. Our results are consistent with the hypothesis that safety nets can be viewed as mechanisms that allow households to take on more risk to pursue higher profits. The results highlight the importance of safety net programs, their effectiveness in ensuring farmers that they will be protected against uninsured shocks, and how that assurance can translate into productivity‐enhancing behavior.     

Adoption of improved maize varieties in the hills of Nepal

Maize (Zea mays L.) is the most important cereal crop in the hills of Nepal, where the grain is used for human consumption and the stover for animal fodder. Maize farms are small, and population pressure necessitates the intensification of existing farming systems. Maize research directed at developing technologies for maize production began in Nepal in 1965. In 2000, a survey was carried out in two districts to determine the current level of adoption of improved maize production practices. In each of these districts, remote and accessible village development committees (VDCs) were surveyed. Questionnaires were administered to 54 randomly selected households in each VDC. A Tobit analysis was used to determine socio‐economic, physical and technology factors that influence the use of improved varieties by farmers. All households use composted farmyard manure, and in the more accessible areas, urea as part of their soil fertility management strategy. Use of improved varieties was less than 60% for all VDCs and only 15% in the most remote VDC. In three of the four VDCs, adoption of improved varieties primarily occurred during the past 5 years. Based on a Tobit analysis, Khet land area, ethnic group, years of fertiliser use, off‐farm income, and contact with extension significantly and positively affected adoption of improved varieties. Farmers in VDCs in central Nepal reported lack of seed to be the major constraint to the adoption of improved varieties, while lack of knowledge of new varieties was the major constraint for farmers in the western VDCs. The results from this survey suggest that the strategy for improving the adoption of new varieties will differ depending on infrastructure and the socio‐economic conditions of the farmers in a given area.     

Comparing Serial,and Choice Task Stated and Inferred Attribute Non‐Attendance Methods in Food Choice Experiments

A number of choice experiment (CE) studies have shown that survey respondents employ heuristics such as attribute non‐attendance (ANA) while evaluating food products. This paper addresses a set of related methodological questions using empirical consumer data from a CE on poultry meat with sustainability labels. First, it assesses whether there are differences in terms of marginal willingness to pay estimates between the two most common ways of collecting stated ANA (serial and choice task level). Second, it validates the self‐reported ANA behaviour across both approaches. Third, it explores the concordance of stated methods with that of the inferred method. Results show that WTP estimates from serial‐level data differ from those from choice task‐level data. Also, self‐reported measures on choice task ANA are found to be more congruent with model estimates than those for serial ANA, as well as with inferred ANA.     

Agricultural technology adoption and child nutrition enhancement: improved maize varieties in rural Ethiopia

Adoption of improved crop varieties can lead to multiple benefits to farm households, including increased productivity, incomes, and food consumption. However, possible impacts of adoption on child nutrition outcomes are rarely explored in the literature. This article helps bridge this gap through an impact assessment of the adoption of improved maize varieties (IMVs) on child nutrition outcomes using a recent household survey from rural Ethiopia. The conceptual linkage between IMV adoption and child nutrition is first established using an agricultural household model. Instrumental variable estimation suggests the overall impacts of adoption on child height‐for‐age and weight‐for‐age z‐scores to be positive and significant. Quantile instrumental variable regressions further reveal that such impacts are largest among children with poorest nutrition outcomes. Finally, by combining a decomposition procedure with system of equations estimation, it is found that the increase in own‐produced maize consumption is the major channel through which IMV adoption affects child nutrition.     

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

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

CAP MTR versus environmentally targeted agricultural policy in marginal arable areas: impact analysis combining simulation and survey data

On June 2003 the final version of the Common Agricultural Policy Mid‐Term Review (CAP MTR) was published. The driving forces of this policy change include inter alia the compliance with World Trade Organization (WTO) negotiations' requirements, improvement of social support for agricultural policy, adjustment to budget constraints and adaptation of agricultural practices to environmental requirements. This article reviews how this policy performs in marginal areas regarding one of those objectives: the provision of environmental outputs related to agricultural activity. As an alternative to this reform, a policy based on agri‐environmental measures designed to maximize environmental outputs, is proposed. Both options are evaluated from a cost‐effectiveness point of view. Data from a farm survey and a positive mathematical programming model for a cereal steppes agro‐system in Spain are combined in order to simulate the effects of this reform and our alternative instrument on several environmental indicators. Results show that in marginal areas, where land abandonment is a clear threat, more environmental output can be achieved for the same cost, while maintaining, if not increasing, the levels of achievement for the other goals.