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The present paper presents a meta-analysis of the economic and agronomic performance of genetically modified (GM) crops worldwide. Bayesian, classical and non-parametric approaches were used to evaluate the performance of GM crops v. their conventional counterparts. The two main GM crop traits (herbicide tolerant (HT) and insect resistant (Bt)) and three of the main GM crops produced worldwide (Bt cotton, HT soybean and Bt maize) were analysed in terms of yield, production cost and gross margin. The scope of the analysis covers developing and developed countries, six world regions, and all countries combined. Results from the statistical analyses indicate that GM crops perform better than their conventional counterparts in agronomic and economic (gross margin) terms. Regarding countries’ level of development, GM crops tend to perform better in developing countries than in developed countries, with Bt cotton being the most profitable crop grown. [ABSTRACT FROM PUBLISHER]

This paper incorporates the milk quota system into technical efficiency analysis of dairy farms in England and Wales. Our approach accounts for milk quota trade, allowing an investigation of the relationship between the way in which milk quota market is used by farmers and technical efficiency. In addition, several explanatory variables for inefficiency were used. Results obtained from a Bayesian stochastic frontier analysis show that the way in which farmers use the milk quota market is linked to farm efficiency. Other aspects such as environmental payments received by the farmer are linked to inefficiency. [ABSTRACT FROM AUTHOR]

This paper analyses the cut flower market as an example of an invasion pathway along which species of non-indigenous plant pests can travel to reach new areas. The paper examines the probability of pest detection by assessing information on pest detection and detection effort associated with the import of cut flowers. We test the link between the probability of plant pest arrivals, as a precursor to potential invasion, and volume of traded flowers using count data regression models. The analysis is applied to the UK import of specific genera of cut flowers from Kenya between 1996 and 2004. There is a link between pest detection and the Genus of cut flower imported. Hence, pest detection efforts should focus on identifying and targeting those imported plants with a high risk of carrying pest species. For most of the plants studied, efforts allocated to inspection have a significant influence on the probability of pest detection. However, by better targeting inspection efforts, it is shown that plant inspection effort could be reduced without increasing the risk of pest entry. Similarly, for most of the plants analysed, an increase in volume traded will not necessarily lead to an increase in the number of pests entering the UK. For some species, such as Carthamus and Veronica, the volume of flowers traded has a significant and positive impact on the likelihood of pest detection. We conclude that analysis at the rank of plant Genus is important both to understand the effectiveness of plant pest detection efforts and consequently to manage the risk of introduction of non-indigenous species.