No abstract

The economics of geographical indications (GIs) is assessed within a vertical product differentiation framework that is consistent with the competitive structure of agriculture. It is assumed that certification costs are needed for GIs to serve as (collective) credible quality certification devices, and production of high‐quality product is endogenously determined. We find that GIs can support a competitive provision of quality and lead to clear welfare gains, although they fall short of delivering the (constrained) first best. The main beneficiaries are consumers. Producers may also accrue some benefit if production of the high‐quality products draws on scarce factors that they own.

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.The Stone index typically used in estimating linear almost ideal demand systems is not invariant to changes in units of measurement, which may seriously affect the approximation properties of the model. A modification to the Stone index, or use of a regular price index instead, are both desirable practices in estimating linear AI models.Key words: almost ideal demand system, index numbers. One of the most commonly used specifications in applied demand analysis is the almost ideal (AI) demand system proposed by Deaton and Muellbauer. A primary reason for the popularity of this model is that, while satisfying a number of desirable properties, it can be approximated at the estimation stage by a linear form. This linear AI model specification typically utilizes a "Stone" price index. Because this linear AI model is not itself derived from a well-specified representation of preferences, this system is of interest only as an approximation to the (integrable) nonlinear AI model.Hence, it is important to ensure good approximation properties for the linear AI model. Unfortunately, as this paper will show, such approximation properties may be seriously affected by the fact that the Stone index is not invariant to the (arbitrary) choice of units of measurement for prices and quantities. AI and Linear AI Demand SystemsDeaton and Muellbauer's AI demand system can be written in share form as Giancarlo Moschini is associate professor of economics, Iowa State University.

The impact on pesticide use of genetically engineered maize and soybean varieties has changed over time.

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A partial-equilibrium, two-country model is developed to analyze implications from the introduction of genetically modified (GM) products. In the model, innovators hold proprietary rights, farmers are (competitive) adopters, some consumers deem GM food to be inferior in quality to traditional food, and the mere introduction of GM crops affects the costs of non-GM food (because of costly identity preservation). Among the results derived, it is shown that, although GM innovations have the potential to improve efficiency, some groups can be made worse off. Indeed, it is even possible that the costs induced by GM innovations outweigh the efficiency gains. Copyright 2004, Oxford University Press.

A three‐region world model for the soybean complex is developed to evaluate the welfare effects of Roundup Ready (RR) soybean adoption. The structural modeling of the innovation accounts for farmers' adoption incentives and for the observed pricing of RR soybean seeds as a proprietary technology. The calibrated model is solved for various scenarios to evaluate the production, price, and welfare impacts of RR soybean adoption. The United States gains substantially from the innovation, with the innovator capturing the larger share of the welfare gains. US farmers benefit in the base scenario, but would be adversely affected if the RR innovation were to increase yields. Spillover of the new technology to foreign competitors erodes the competitive position of domestic soybean producers, and export of the technology per se may not improve the welfare position of the innovating country. Consumers in every region gain from the adoption of RR soybeans. [JEL Classification: F14, O33, Q16]. © 2000 John Wiley & Sons, Inc.

We study firm reputation as a mechanism to assure product quality in perfectly competitive markets in a context in which both certification and trademarks are available. Shapiro's (1983) model of reputation is extended to reflect both collective and firm-specific reputations, and this framework is used to study certification and trademarks for food products with a regional identity, known as geographical indications (GIs). Our model yields two primary results. First, in markets with asymmetric information and moral hazard problems, credible certification schemes reduce the cost of establishing reputation and lead to welfare gains compared to a situation in which only private trademarks are available. Hence, certification improves the ability of reputation to operate as a mechanism for assuring quality. Second, the actual design of the certification scheme plays an important role in mitigating informational problems. From a policy perspective, our results have implications for the current debate and negotiations on GIs at the World Trade Organization and the ongoing product quality policy reform within the European Union. With regard to the instrument of choice to provide intellectual property protection for GIs, our model favors a sui generis scheme based on appellations over certification marks. Finally, our model supports the validity of the traditional specialities guaranteed scheme of the European Union as an instrument for the provision of high-quality products that are not linked to a geographic area.