To what extent can the future price of icon wines be anticipated from information available at the time of their initial sale by wineries? Using a seemingly unrelated regression model we show that weather variables and changes in production techniques, along with the age of the wine, have significant power in explaining the secondary market price variation across different vintages of each of three icon Australian red wines. The results have implications for winemakers in determining the prices they pay for grapes and charge for their wines, and for consumers/wine investors as a guide to the prospective quality of immature icon wines. (JEL codes: C23, D12, D44, D80, G12)

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Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

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Global participation in space activity is growing as satellite technology matures and spreads. Countries in Africa, Asia and Latin America are creating or reinvigorating national satellite programs. These countries are building local capability in space through technological learning. They sometimes pursue this via collaborative satellite development projects with foreign firms that provide training. This phenomenon of collaborative satellite development projects is poorly understood by researchers of technological learning and technology transfer. The approach has potential to facilitate learning, but there are also challenges due to misaligned incentives and the tacit nature of the technology. Perspectives from literature on Technological Learning, Technology Transfer, Complex Product Systems and Product Delivery provide useful but incomplete insight for decision makers in such projects. This work seeks a deeper understanding of capability building through collaborative technology projects by conceiving of the projects as complex, socio-technical systems with architectures. The architecture of a system is the assignment of form to execute a function along a series of dimensions. The research questions explore the architecture of collaborative satellite projects, the nature of capability building during such projects, and the relationship between architecture and capability building. The research design uses inductive, exploratory case studies to investigate six collaborative satellite development projects. Data collection harnesses international field work driven by interviews, observation, and documents. The data analysis develops structured narratives, architectural comparison and capability building assessment. The architectural comparison reveals substantial variation in project implementation, especially in the areas of project initiation, technical specifications of the satellite, training approaches and the supplier selection process. The individual capability building assessment shows that most trainee engineers gradually progressed from no experience with satellites through theoretical training to supervised experience; a minority achieved independent experience. At the organizational level, the emerging space organizations achieved high levels of autonomy in project definition and satellite operation, but they were dependent on foreign firms for satellite design, manufacture, test and launch. The case studies can be summarized by three archetypal projects defined as "Politically Pushed," "Structured," and "Risk Taking." Countries in the case studies tended to start in a Politically Pushed mode, and then moved into either Structured or Risk Taking mode. Decision makers in emerging satellite programs can use the results of this dissertation to consider the broad set of architectural options for capability building. Future work will continue to probe how specific architectural decisions impact capability building outcomes in satellite projects and other technologies.

Malaria and other vector borne diseases claim lives and cause illness, especially in less developed countries. Although well understood methods, such as spraying and insecticidal nets, are identified as effective deterrents to malaria transmission by mosquitos, the nations that have the greatest burden from the disease also struggle to deploy such measures sufficiently. More targeted and up to date information is needed to identify which regions of malariaendemic countries are most likely to be at risk of malaria in the near future. This will allow national governments, local officials and public health workers to deploy protective equipment and personnel where they are most needed. This paper explores the role of environmental data generated via satellite remote sensing as an ingredient to a Malaria Early Warning System. Data from remote sensing satellites can cover broad geographical areas frequently and consistently. Much of the relevant data may be accessed by malaria-endemic countries at minimal cost via international data sharing polices. While previous research studies have demonstrated the potential to assign malaria risk to a geographic region based on indicators from satellites and other sources, there is still a need to deploy such tools in a broader and more operational manner to inform decision making on malaria management. This paper describes current research on the use of satellite-based environmental data to predict malaria risk and examines the barriers and opportunities for implementing Malaria Early Warning Systems enabled by satellite remote sensing. A Systems Architecture framework analyses the components of a Malaria Early Warning System and highlights the need for effective coordination across public and private sector organizations.