Modelling Spikes in Electricity Prices

uring periods of market stress, electricity prices can rise dramatically. Electricity retailers cannot pass these extreme prices on to customers because of retail price regulation. Improved prediction of these price spikes therefore is important for risk management. This paper builds a time-varying-probability Markov-switching model of Queensland electricity prices, aimed particularly at forecasting price spikes. Variables capturing demand and weather patterns are used to drive the transition probabilities. Unlike traditional Markov-switching models that assume normality of the prices in each state, the model presented here uses a generalised beta distribution to allow for the skewness in the distribution of electricity prices during high-price episodes.

Assessing the impact of floods and flood legislation on residential property prices

The changing development and population sprawl in major cities, especially those located in high rainfall areas, has resulted in the need to review and re-assess potential flood impacts in these cities. In many cases these new flood lines and flood maps have placed residential property that was previously considered to be flood free to now be considered to be potentially flood liable. Previous research based in Sydney and the UK has identified the fact that residential property that has been subject to flooding has a decreased price and higher investment risk than flood free property in the same location. These studies have also shown that the greatest impact on residential property subject to flooding is just following a flood event. In June 2009, Brisbane City Council released revised flood maps for the Greater Brisbane region and these maps have identified areas that have not previously been considered flood liable. This paper will analyse the sale performance of flood liable streets in the main flood areas of Brisbane over the period January 1990 through to June 2009, to determine the variation in price for these flood liable areas to the residential property immediately adjoining them. The average sale price will be tracked on both a geographic location and socio-economic basis.

NSW rural land performance : 1990-2008

The annual income return for rural property is based on two major factors being commodity prices and production yields. Commodity prices paid to rural producers can vary depending on the agricultural policies of their respective countries. Free trade countries, such as Australia and New Zealand are subject to the volatility of the world commodity markets to a greater extent than those farmers in protected or subsidised markets. In countries where rural production is protected or subsidised the annual income received by rural producers has been relatively stable. However, the high cost of agricultural protection is now being questioned, particularly in relation to the increasing economic costs of government services such as health, education and housing. When combined with the agricultural production limitations of climate, topography, chemical residues and disease issues, the impact of commodity prices on rural property income is crucial in the ability of rural producers to enter into or expand their holdings in agricultural land. These problems are then reflected in the volatility of the rural land capital returns and the investment performance of this property class. This paper will address the total and capital return performance of a major agricultural area and compare these returns on the basis of both location of land and land use. The comparison will be used to determine if location or actual land use has a greater influence on rural property capital returns. This performance analysis is based on over 35,000 rural sales transactions. These transactions cover all market based rural property transactions in New South Wales, Australia for the period January 1990 to December 2008. Correlation analysis and investment performance analysis has also been carried out to determine the possible relationships between location and land use and subsequent changes in rural land capital values.

Implicit discount rates and fisheries management : is there a relationship?

Fishers are faced with multiple risks, including unpredictability of future catch rates, prices and costs. While the latter are largely beyond the control of fisheries managers, effective fisheries management should reduce uncertainty about future catches. Different management instruments are likely to have different impacts on the risk perception of fishers, and this should manifest itself in their implicit discount rate. Assuming licence and quota values represent the net present value of the flow of expected future profits, then a proxy for the implicit discount rate of vessels in a fishery can be derived by the ratio of the average level of profits to the average licence/quota value. From this, an indication of the risk perception can be derived, assuming higher discount rates reflect higher levels of systematic risk. In this paper, we apply the capital asset pricing model (CAPM) to determine the risk premium implicit in the discount rates for a range of Australian fisheries, and compare this with the set of management instruments in place. We test the assumption that rights based management instruments lower perceptions of risk in fisheries. We find little evidence to support this assumption. although the analysis was based on only limited data.

N2O emissions from agricultural lands: a synthesis of simulation approaches

Nitrous oxide (N2O) is primarily produced by the microbially-mediated nitrification and denitrification processes in soils. It is influenced by a suite of climate (i.e. temperature and rainfall) and soil (physical and chemical) variables, interacting soil and plant nitrogen (N) transformations (either competing or supplying substrates) as well as land management practices. It is not surprising that N2O emissions are highly variable both spatially and temporally. Computer simulation models, which can integrate all of these variables, are required for the complex task of providing quantitative determinations of N2O emissions. Numerous simulation models have been developed to predict N2O production. Each model has its own philosophy in constructing simulation components as well as performance strengths. The models range from those that attempt to comprehensively simulate all soil processes to more empirical approaches requiring minimal input data. These N2O simulation models can be classified into three categories: laboratory, field and regional/global levels. Process-based field-scale N2O simulation models, which simulate whole agroecosystems and can be used to develop N2O mitigation measures, are the most widely used. The current challenge is how to scale up the relatively more robust field-scale model to catchment, regional and national scales. This paper reviews the development history, main construction components, strengths, limitations and applications of N2O emissions models, which have been published in the literature. The three scale levels are considered and the current knowledge gaps and challenges in modelling N2O emissions from soils are discussed.

Didiman: Australian agricultural extension officers in the territory of Papua and New Guinea, 1945-1975

Historically, the development philosophy for the two Territories of Papua and New Guinea (known as TPNG, formerly two territories, Papua and New Guinea) was equated with economic development, with a focus on agricultural development. To achieve the modification or complete change in indigenous farming systems the Australian Government’s Department of External Territories adopted and utilised a programme based on agricultural extension. Prior to World War II, under Australian administration, the economic development of these two territories, as in many colonies of the time, was based on the institution of the plantation. Little was initiated in agriculture development for indigenous people. This changed after World War II to a rationale based on the promotion and advancement of primary industry, but also came to include indigenous farmers. To develop agriculture within a colony it was thought that a modification to, or in some cases the complete transformation of, existing farming systems was necessary to improve the material welfare of the population. It was also seen to be a guarantee for the future national interest of the sovereign state after independence was granted. The Didiman and Didimisis became the frontline, field operatives of this theoretical model of development. This thesis examines the Didiman’s field operations, the structural organisation of agricultural administration and the application of policy in the two territories.

Reconciling the supply of and demand for carbon cycle science in the US agricultural sector

When asking the question, ``How can institutions design science policies for the benefit of decision makers?'' Sarewitz and Pielke Sarewitz, D., Pielke Jr., R.A., this issue. The neglected heart of science policy: reconciling supply of and demand for science. Environ. Sci. Policy 10] posit the idea of ``reconciling supply and demand of science'' as a conceptual tool for assessment of science programs. We apply the concept to the U.S. Department of Agriculture's (USDA) carbon cycle science program. By evaluating the information needs of decision makers, or the ``demand'', along with the supply of information by the USDA, we can ascertain where matches between supply and demand exist, and where science policies might miss opportunities. We report the results of contextual mapping and of interviews with scientists at the USDA to evaluate the production and use of current agricultural global change research, which has the stated goal of providing ``optimal benefit'' to decision makers on all levels. We conclude that the USDA possesses formal and informal mechanisms by which scientists evaluate the needs of users, ranging from individual producers to Congress and the President. National-level demands for carbon cycle science evolve as national and international policies are explored. Current carbon cycle science is largely derived from those discussions and thus anticipates the information needs of producers. However, without firm agricultural carbon policies, such information is currently unimportant to producers. (C) 2006 Elsevier Ltd. All rights reserved.

Diversity of Cicadellidae in agricultural production areas in the Ovens Valley, Northeast Victoria, Australia

There is a paucity of data on the distribution of Cicadellidae (leafhoppers) in Australia. This study quantifies the relative abundance, seasonal activity and diversity of leafhoppers in the Ovens Valley region of north-east Victoria, Australia. Species diversity and abundance was assessed at four field sites in and around the field borders of commercially grown tobacco crops using three sampling techniques (pan trap, sticky trap and sweep net). Over 51 000 leafhopper samples were collected, with 57 species from 11 subfamilies and 19 tribes identified. Greater numbers and diversity of leafhoppers were collected in yellow pan traps. The predominant leafhopper collected was Orosius orientalis (Matsumura). Twenty-three leafhopper species were recorded for the first time in Victoria and eight economically important pest species were recorded. Seasonal activity of selected leafhopper species, covering two sampling seasons, is presented.

Participatory design for technological disruption within the agricultural sector

Agricultural adoption of innovation has traditionally been described as slow to diffuse. This paper therefore describes a case study grounded in PD to address a disruptive technology/system within the livestock industry. Results of the process were positive, as active engagement of stakeholders returned rich data. The contribution of the work is also presented as grounds for further design research in the livestock industry.

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design