Summary Environmental monitoring is becoming increasingly sophisticated with the widespread adoption of data loggers, sensor arrays and remote sensing, leading to larger scale, higher resolution and superior quality data. However, interpreting monitoring data and deciding when and how to apply environmental management remains a subjective and underdeveloped area of research. Control charts, developed in industrial settings to identify when manufacturing processes were beyond the acceptable bounds of production quality, represent one solution. Despite their potential utility, control charts have rarely been adopted in environmental monitoring. In theory, they are able to identify undesirable trends early and provide transparent and broadly consensual criteria for defining when management action should take place, that is action is triggered when parameter values are observed beyond the agreed control limits of the process. Once triggered, a predetermined management action is implemented. Possible actions are many and varied, and range from investigation and increased monitoring to intervention in the system. Here, the utility of control charts in monitoring water supply in south‐western Australia from 1911 to 2010 is examined, and their ability to provide an early, transparent and easily understandable means of triggering management action is assessed. Two control chart types are applied: the X ‐bar chart and the CUSUM chart. X ‐bar charts varied widely in their ability to trigger action and were insensitive to many traditional threshold criteria (of which there are many to choose from). In contrast, standard CUSUM charts are specifically designed to detect subtler shifts away from a mean trend and hence provided a more consistent warning of the decline in water supply. While managers were aware of the decline in water supply from an early stage, we believe that control charts could have clearly communicated this earlier, enabling consensus among decision makers to be reached more rapidly.
Abstract In the literature, there is no standard approach for estimating the return to wine or testing for a portfolio risk diversification benefit from holding wine. Using auction data for Australian wine, we show that the estimation method has a material impact on the estimated wine return distribution and that the type of diversification benefit test used influences whether or not wine is found to provide a portfolio risk diversification benefit. Our results indicated that a simple modification to the hedonic model, which we call a pooled model, is an appropriate method for estimating the return to infrequently traded heterogeneous assets such as wine. Across the various approaches to testing for a risk diversification benefit, we find direct estimation of the efficient frontier with bootstrapped confidence intervals to be the most transparent and comprehensive method of illustrating wine's potential for lowering portfolio risk. (JEL Classifications: G11, C61, C13)
Increasing pressure to reduce the use of pre and post-harvest treatment chemicals to control insect pests has led to calls for alternative control methods. As a result, the implementation of area-wide management of pests could be developed as either an alternative to chemicals or as a means of reducing pesticide use. However, maintaining an area-wide management programme can be expensive as it requires the execution of surveillance activities, exclusion measures and contingency plans for a rapid eradication response in the case of a pest outbreak. A sound benefit-cost analysis is an essential starting point to measure gains from research and development into improved methods of surveillance and exclusion. This paper presents a study of the costs of surveillance measures. We applied our model to the Fruit Fly Exclusion Zone (FFEZ) in South Eastern Australia.
In this paper, we estimate the effect of tree canopy cover on sales price of urban residential properties in P erth, W estern A ustralia. Using a data set of 5606 single family homes sold in 2009 and a spatial hedonic model with three spatial effects – spatial‐temporal lag on dependent variable, spatial error, and spatially lagged independent variables – we estimated the location‐specific effect of tree canopy cover. Tree canopy cover increases the property value when located on adjacent public space, but decreases the value when it is on own property and on the adjacent property within 20 m of property boundary. The results are suggestive that council urban tree planting programs provide significant private benefits to homeowners.
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This paper presents a spatially explicit analysis of the contribution of urban trees and parks to residential property values. We estimated the effects of structural, neighbourhood, and environmental variables, including tree cover, on sale price of single-family homes in Perth using a generalized spatial two-stage least-squares model. The spatial model results indicate that, among other structural and neighbourhood variables, the proportion of tree cover on street verges (public space) and the extent and proximity of neighbourhood parks attract significant price premiums in the Perth housing market. However, we failed to find any evidence of impact of the tree cover on property (private space) on its sale price. Further, we find that the parameter estimate for street tree cover obtained from spatial hedonic model is half the size of estimate obtained from ordinary hedonic model, thus indicating importance of spatially explicit hedonic model on implicit price estimation. Based on the spatial hedonic model, it is estimated that 10% increase in tree cover on street verge above the median cover of 19.66% increases the median house price (AU$ 765,000) by about AU$ 3,250. Our findings have implications on managing and developing urban forest cover along the streets in Perth for both private and public benefits.
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