T.M. Swanson – författare

The advent of new biotechnologies implies significant changes in the world, both biologically and industrially. Biologically, these new technologies represent changes on a scale never before witnessed in the context of evolutionary systems. How these systems will respond to these changes is uncertain and potentially very significant. The first part of this volume addresses these issues in a series of chapters considering the manner in which societies might analyse and manage these systemic responses to biotechnological changes. The second part of the volume addresses the industrial issues concerning biotechnologies. One of the primary motivations for these changes is to enhance the appropriability of the value of innovation occurring within the life sciences sectors. Changing to a property rights-based system of biotechnology has implications for the nature of research and development within these sectors, and the diffusion and distribution of its benefits across the globe. Another set of chapters in this volume sets out a framework for considering these important industrial issues. The volume is the outcome of a two-year project on the economics of managing biotechnologies in agriculture. It is recommended to academics and policy makers interested in the issues concerning society's options in the management of this process of technological change.

The marginal price elasticities estimated by Martinez-Espineira conforms to expectation. The price specification that accounts for the changing proportion of water users in each block yields a higher elasticity (-0. 47) compared to the spec­ ification ignoring this feature of the data. However, this difference is not found to be statistically significant, a result attributed to the low power of the test (small sample size limiting the accuracy of estimates). In conclusion, the paper provides a theoretically correct price specification for demand functions under block pricing and aggregate data. The empirical findings in the paper, however, are not conclusive and further empirical work using more data and alternative (nonlinear) demand functions, is needed to show the practical implications of the arguments put forward by the Martinez-Espineira's paper. Static empirical consumer demand functions estimated with aggregate data are well known to suffer form serial correlation and other statistical problems asso­ ciated with misspecified dynamics. These dynamics arise because consumers do not react immediately to a change in prices due to their largely predetermined lifestyle. In the case of demand for water, for example, current purchases can be largely predetermined due to commitments arising from past purchases such as swimming pools, bathtubs, dishwashing machines, etc. Muellbauer and Pashardes (1992) show that the autoregressive nature of consumer demand data can be cap­ tured in a theoretically consistent manner by incorporating intertemporal aspects of consumer behaviour in the model through habit formation and durability.

The marginal price elasticities estimated by Martinez-Espineira conforms to expectation. The price specification that accounts for the changing proportion of water users in each block yields a higher elasticity (-0. 47) compared to the spec­ ification ignoring this feature of the data. However, this difference is not found to be statistically significant, a result attributed to the low power of the test (small sample size limiting the accuracy of estimates). In conclusion, the paper provides a theoretically correct price specification for demand functions under block pricing and aggregate data. The empirical findings in the paper, however, are not conclusive and further empirical work using more data and alternative (nonlinear) demand functions, is needed to show the practical implications of the arguments put forward by the Martinez-Espineira's paper. Static empirical consumer demand functions estimated with aggregate data are well known to suffer form serial correlation and other statistical problems asso­ ciated with misspecified dynamics. These dynamics arise because consumers do not react immediately to a change in prices due to their largely predetermined lifestyle. In the case of demand for water, for example, current purchases can be largely predetermined due to commitments arising from past purchases such as swimming pools, bathtubs, dishwashing machines, etc. Muellbauer and Pashardes (1992) show that the autoregressive nature of consumer demand data can be cap­ tured in a theoretically consistent manner by incorporating intertemporal aspects of consumer behaviour in the model through habit formation and durability.

The marginal price elasticities estimated by Martinez-Espineira conforms to expectation. The price specification that accounts for the changing proportion of water users in each block yields a higher elasticity (-0. 47) compared to the spec­ ification ignoring this feature of the data. However, this difference is not found to be statistically significant, a result attributed to the low power of the test (small sample size limiting the accuracy of estimates). In conclusion, the paper provides a theoretically correct price specification for demand functions under block pricing and aggregate data. The empirical findings in the paper, however, are not conclusive and further empirical work using more data and alternative (nonlinear) demand functions, is needed to show the practical implications of the arguments put forward by the Martinez-Espineira''s paper. Static empirical consumer demand functions estimated with aggregate data are well known to suffer form serial correlation and other statistical problems asso­ ciated with misspecified dynamics. These dynamics arise because consumers do not react immediately to a change in prices due to their largely predetermined lifestyle. In the case of demand for water, for example, current purchases can be largely predetermined due to commitments arising from past purchases such as swimming pools, bathtubs, dishwashing machines, etc. Muellbauer and Pashardes (1992) show that the autoregressive nature of consumer demand data can be cap­ tured in a theoretically consistent manner by incorporating intertemporal aspects of consumer behaviour in the model through habit formation and durability.