The impact of social networks on hybrid seed adoption in India

This article adds to the literature about the impact of social networks on the adoption of modern seed technologies among smallholder farmers in developing countries. The analysis centers on the adoption of hybrid wheat and hybrid pearl millet in India. In the local context, both crops are cultivated mainly on a subsistence basis, and they provide examples of hybrid technologies at very different diffusion stages: while hybrid wheat was commercialized in India only in 2001, hybrid pearl millet was launched in 1965. The analysis is based on surveys of wheat and millet farmers in the state of Maharashtra. Comprehensive data on farmer characteristics and social interactions allow for identifying individual networks, thereby improving upon previous research approaches that employed village-level variables as proxies for network effects. Using econometric models, we find that individual social networks play an important role for technology adoption decisions. While village-level variables may be used as suitable proxies at later diffusion stages, they tend to underestimate the role of individual networks during early phases of adoption.     

Genetically Modified Crops and Product Differentiation: Trade and Welfare Effects in the Soybean Complex

A partial equilibrium four-region world trade model for the soybean complex is developed in which Roundup Ready (RR) products are weakly inferior substitutes to conventional ones, RR seeds are priced at a premium, and costly segregation is necessary to separate conventional and biotech products. Solution of the calibrated model illustrates how incomplete adoption of RR technology arises in equilibrium. The United States, Argentina, Brazil, and the Rest of the World (ROW) all gain from the introduction of RR soybeans, although some groups may lose. The impacts of RR production or import bans by the ROW or Brazil are analyzed. U.S. price support helps U.S. farmers, despite hurting the United States and has the potential to improve world efficiency.     

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.     

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.     

Will the TRIPS Agreement Foster Appropriate Biotechnologies for Developing Countries?

While almost all of the investment in agricultural biotechnology to date has been in temperate crops suitable for developed countries, developing countries are the greatest potential beneficiaries of this major technological advance. To realise this potential requires investment in crops appropriate to climatic and agronomic conditions in developing countries. Protection of intellectual property rights is a necessary condition for the private sector to invest in appropriate biotechnologies. This paper develops a game theoretic model of a bioscience firm that adapts a new technology to a range of agronomic conditions in response to the enforcement of intellectual property rights in a developed and a developing country. Over a range of potential penalties, low levels of enforcement by the developing country remain endemic despite the desire to have the bioscience firm adapt the biotechnology to its local conditions. In particular, the trade penalties contained in the Agreement on Trade‐Related Aspects of Intellectual Property Rights are likely to be ineffective. The developing country might increase enforcement if the developed country was more aggressive in liberalising agriculture trade because there would be greater symmetry in the benefits of the technology.     

Explaining agricultural productivity growth: an international perspective

This article presents multi-output, multi-input total factor productivity (TFP) growth rates in agriculture for 88 countries over the 1970–2001 period, estimated with both stochastic frontier analysis (SFA) and the more commonly employed data envelopment analysis (DEA). We find results with SFA to be more plausible than with DEA, and use them to analyze trends across countries and the determinants of TFP growth in developing countries. The central finding is that policy and institutional variables, including public agricultural expenditure and proagricultural price policy reforms, are significant correlates of TFP growth. The most significant geographic correlate of TFP growth is distance to the nearest OECD country.     

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.     

Forecasting the Adoption of GM Oilseed Rape: Evidence from a Discrete Choice Experiment in Germany

This paper explores farmers’ willingness to adopt genetically modified (GM) oilseed rape prior to its commercial release and estimates the ‘demand’ for the new technology. The analysis is based upon choice experiments with 202 German arable farmers. A multinomial probit estimation reveals that GM attributes such as gross margin, expected liability from cross pollination, or flexibility in returning to conventional oilseed rape significantly affect the likelihood of adoption. Neighbouring farmers’ attitudes towards GM cropping and a number of farmer and farm characteristics were also found to be significant determinants of prospective adoption. Demand simulations suggest that adoption rates are very sensitive to the profit difference between GM and non‐GM rape varieties. A monopolistic seed price would substantially reduce demand for the new technology. A monopolistic seed supplier would reap between 45% and 80% of the GM rent, and the deadweight loss of the monopoly would range between 15% and 30% of that rent. The remaining rent for farmers may be too small to outweigh possible producer price discounts resulting from the costs of segregating GM and non‐GM oilseed rape along the supply chain.     

Factors explaining the diffusion of hybrid maize in Latin America and the Caribbean region

If future demand for maize in Latin America and the Caribbean region (LAC) is to be met from local sources, domestic production must continue to increase. Because further expansion in the area planted to maize is precluded by the limited availability of arable land, future increases in production will have to rely heavily on the spread of productivity‐enhancing hybrid technology. Until now, the diffusion of hybrid maize in LAC has been quite variable. Using data from 18 countries, we investigate factors affecting the hybrid maize diffusion rate. Our findings validate conventional profitability‐based explanations of producer adoption behavior, but they also confirm the importance of supply‐side factors, thereby providing empirical support for the life cycle theory of seed industry development. We conclude that if policy makers in LAC are to accelerate the diffusion of hybrid maize, they will have to ensure an environment in which it is not only profitable for producers to adopt improved germplasm, but also profitable for the seed industry to produce and sell high‐quality seed.     

Estimating returns to soil conservation adoption in the northern Ethiopian highlands

Land degradation in the form of soil erosion and nutrient depletion presents a threat to food security and sustainability of agricultural production in many developing countries. Governments and development agencies have invested substantial resources to promote soil conservation practices as part of an effort to improve environmental conditions and reduce poverty. However, limited rigorous empirical work has been done on the economics of soil conservation technology adoption. This article investigates the impact of stone bunds on value of crop production per hectare in low and high rainfall areas of the Ethiopian highlands using cross-sectional data from more than 900 households, with multiple plots per household. We have used modified random effects models, stochastic dominance analysis (SDA), and matching methods to ensure robustness. The parametric regression and SDA estimates are based on matched observations obtained from the nearest neighbor matching using propensity score estimates. This is important, because conventional regression and SDA estimates are obtained without ensuring that there actually exist comparable conserved and nonconserved plots on the distribution of covariates. We use matching methods, random effects, and Mundlak's approach to control selection and endogeneity bias that may arise due to correlation of unobserved heterogeneity and observed explanatory variables.
We find that the three methods tell a consistent story. Plots with stone bunds are more productive than those without such technologies in semi-arid areas but not in higher rainfall areas, apparently because the moisture conserving benefits of this technology are more beneficial in drier areas. This implies that the performance of stone bunds varies by agro-ecology type, suggesting the need for designing and implementing appropriate site-specific technologies.     

Protecting Biotechnology IPRs in Developing Countries: Simple Analytics of a Levy Solution

High transaction costs and an absence of institutional infrastructure in developing countries prevent comprehensive enforcement of intellectual property rights and generate obstacles to the adoption of genetically modified (GM) crop technology. Governments of developing countries that are members of the World Trade Organization are faced with two options when licensing GM crop technology: (1) attempt to regulate GM crops to the standards of the Agreement on Trade‐Related Aspects of Intellectual Property (TRIPS) or (2) allow a black market in GM seeds and risk trade retaliation from the GM innovator's host country through a TRIPS trade complaint. This paper develops a conceptual model that frames the adopting country's range of licensing options, including a new levy system, and derives welfare measures for each option. The model illustrates how a levy on GM technology can be a welfare‐increasing policy for developing countries, and the operation of a levy is discussed. The conceptual model is applied to Brazil's soybean market and quantitative economic surplus measures are estimated within a calibrated welfare model for a range of licensing scenarios. The model's results suggest that a levy may interfere with the long‐term prospects for innovators to collect monopoly rents in adopting countries.     

ICT and agricultural productivity: evidence from cross-country data

This article carries out agricultural production function estimations, based on data for the period 1995–2000 on 81 countries, to present empirical evidence on the relationship between the adoption of information and communication technology (ICT) and agricultural productivity. It is found that new ICT has a significantly positive impact on agricultural productivity. The evidence suggests that the adoption of modern industrial inputs in agricultural production relies on the information and communication infrastructure. However, the empirical evidence from this study also suggests that new ICT could be a factor for the divergence between countries in terms of overall agricultural productivity. Not only do we find that the ICT adoption levels of the richer countries are much higher than those of the poorer countries, but also that returns from ICT in agricultural production of the richer countries are about two times higher than those of the poorer countries. A plausible explanation for the poorer countries' relatively low productivity elasticity of ICT is the lack of important complementary factors, such as a substantial base of human capital.     

Food Regime Analysis in a Post‐Neoliberal Era: Argentina and the Expansion of Transgenic Soybeans

This paper uses the food regime literature to analyse the political and economic relations promoting the expansion of soybeans in Argentina following the post‐neoliberal turn in the early 2000s. Continuities of the agrarian expansion from the neoliberal to post‐neoliberal model highlight the state's role in supporting a neoliberal food regime. Neoregulation in the post‐neoliberal agenda continues to favour increased production of transgenic food over ecological and human‐health considerations. Moreover, the emergence of new corporate and transnational actors has contributed to a new form of corporate‐agrarian governance premised on biotechnology. First, a food regime lens is used to describe the expansion of transgenic soybeans in Argentina, followed by an analysis of planning documents to show the state's position in reproducing neoliberal discourses and policies favouring the expansion of agriculture. The conclusion discusses the utility of food regime analysis for explaining the new forms of agricultural governance in Argentina.     

Acceptance of genetically modified food: comparing consumer perspectives in the United States and South Korea

This study examines public perceptions of biotechnology, specifically the consumer approval of genetically modified food products, from plant as well as from animal origin, based on data collected from national surveys conducted in both the United States and South Korea. South Korean consumers reported better understanding of food production, science, and technology relative to U.S. consumers. South Korean consumers also recalled having heard more about genetic modification than did U.S. consumers. Findings also suggest that consumers in the United States and South Korea who possessed an accurate knowledge of the applications and outcomes of genetic modification technology were more likely to approve of its use for the creation of foods than those who had inaccurate or no knowledge of the technology. Results also indicate that consumers who considered labeling of genetically modified foods to be necessary are less likely to approve of the genetic modification of foods than those who did not. Consumers in both countries are less approving of genetic modification of animals than the genetic modification of plants. However, U.S. consumers are more approving of using genetic modification technology to create animal‐derived foods than are South Korean consumers.     

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.     

Linking of U.S. monetary policy and exchange rates to world soybean markets

The linkage between macroeconomic policies and agricultural commodity trade has become an important research issue of agricultural economists. This paper investigates the macroeconomic linkage of soybean trade competition between the exporting countries of the United States, Brazil, and Argentina in the EC-12 and Japan import markets. It is argued that U.S. monetary growth may have important impacts on the competitive position of U.S. soybean exports through exchange rates. Two relationships are investigated: (a) the effects of U.S. monetary growth on the agricultural trade weighted exchange rates, and (b) the responsiveness of agricultural commodity prices and U.S. exports to exchange rate movements. Results indicate that a weak dollar increases imports of soybeans and soymeal significantly which serves to increase the equilibrium world price and increase both U.S. and Brazil/Argentina exports in the long run. However, during periods of more expansionary U.S. monetary policy there is little evidence of significant increases in market share position for U.S. soybeans and soymeal in world markets.     

Taking a new look at empirical models of adoption: average treatment effect estimation of adoption rates and their determinants

This article shows that the observed sample adoption rate does not consistently estimate the population adoption rate even if the sample is random. It is proved that instead the sample adoption rate is a consistent estimate of the population joint exposure and adoption rate, which does not inform about adoption per se. Likewise, it is shown that a model of adoption with observed adoption outcome as a dependent variable and where exposure to the technology is not observed and controlled for cannot yield consistent estimates of the determinants of adoption. The article uses the counterfactual outcomes framework to show that the true population adoption rate corresponds to what is defined in the modern policy evaluation literature as the average treatment effect (ATE), which measures the effect or impact of a "treatment" on a person randomly selected in the population. In the adoption context, a "treatment" corresponds to exposure to the technology. The article uses the ATE estimation framework to derive consistent nonparametric and parametric estimators of population adoption rates and their determinants and applies the results to consistently estimate the population adoption rates and determinants of the NERICA (New Rice for Africa) rice varieties in Côte d'Ivoire. The ATE methodological approach developed in the article has significant policy implications with respect to judging the intrinsic merit of a new technology in terms of its potential demand by the target population independently of issues related to its accessibility and in terms of the decision to invest or not in its wide-scale dissemination.     

Analyzing technology adoption using microstudies: limitations, challenges, and opportunities for improvement

Policy makers and interest groups have many questions about the use of improved technologies in developing country agriculture. These include the roles of policies, institutions, and infrastructure in the adoption of improved technologies and their impact on productivity and welfare. Most micro‐level adoption studies, however, cannot address these important policy issues. Drawing on an extensive review of the literature on the adoption of agricultural technologies, this article suggests alternative approaches for designing technology adoption studies to make them useful for policy makers. It explores the generic limitations of cross‐sectional adoption studies carried out in small numbers of communities and discusses some problems faced in conducting such studies. Recommendations include the use of sampling approaches that allow data from microstudies to be generalized to higher levels of aggregation, adherence to clearly defined terms that are standardized across studies, and careful examination of the assumptions that often underlie such studies.     

Comparative Advantage in Demand: Experimental Evidence of Preferences for Genetically Modified Food in the United States and European Union

The United States (US) exports more than US$6 billion in agricultural commodities to the European Union(EU) each year, but one issue carries the potential to diminish this trade: use of biotechnology in food production. The EU has adopted more stringent policies towards biotechnology than the US. Understanding differences in European and American policies towards genetically modified (GM) foods requires a greater understanding of consumers’ attitudes and preferences. This paper reports results from the first large‐scale, cross‐Atlantic study to analyse consumer demand for genetically modified food in a non‐hypothetical market environment. We strongly reject the frequent if convenient assumption in trade theory that consumer preferences are identical across countries: the median level of compensation demanded by English and French consumers to consume a GM food is found to be more than twice that in any of the US locations. Results have important implications for trade theory, which typically focuses on differences in specialization, comparative advantage and factor endowments across countries, and for on‐going trade disputes at the World Trade Organization.     

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.