Weekly prices of butter on the Elgin Board of Trade /

Description based on: 1885-1916.

The eggs of marine crabs - an unexploited resource

Marine crabs belonging to the family Portunidae form bycatch of shrimp trawlers in India. They are sold at low prices and consumers discard eggs and consume the meat. The paper details the nutritional value of eggs of Portunus pelagicus.

The relationship between central market egg reports and producer prices in selected North Central states /

"The research on which this report is based was undertaken as part of the North Central Regional Poultry Marketing Project NCM-14."--P. [3].

Data mining on prices of highway project main material based on WEB

The management of main material prices of provincial highway project quota has problems of lag and blindness. Framework of provincial highway project quota data MIS and main material price data warehouse were established based on WEB firstly. Then concrete processes of provincial highway project main material prices were brought forward based on BP neural network algorithmic. After that standard BP algorithmic, additional momentum modify BP network algorithmic, self-adaptive study speed improved BP network algorithmic were compared in predicting highway project main prices. The result indicated that it is feasible to predict highway main material prices using BP NN, and using self-adaptive study speed improved BP network algorithmic is the relatively best one.

Modelling Wages and Prices in Australia

This paper estimates a simultaneous-equation model of wages and prices for Australia, underpinned by a competing claims framework of imperfect competition. Two separate co-integrating relationships for wages and prices are identified by imposing the economic hypotheses implied by the theory. The steady-state relationships for wages and prices are then embedded in a parsimonious, dynamic wage-price model. The final model is both simple and parsimonious and able to describe the process of wage and price inflation in Australia

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.

Infrastructure charges and increases to new house prices : a preliminary analysis of the US empirical models

Sourcing appropriate funding for the provision of new urban infrastructure has been a policy dilemma for governments around the world for decades. This is particularly relevant in high growth areas where new services are required to support swelling populations. The Australian infrastructure funding policy dilemmas are reflective of similar matters in many countries, particularly the United States of America, where infrastructure cost recovery policies have been in place since the 1970’s. There is an extensive body of both theoretical and empirical literature from these countries that discusses the passing on (to home buyers) of these infrastructure charges, and the corresponding impact on housing prices. The theoretical evidence is consistent in its findings that infrastructure charges are passed on to home buyers by way of higher house prices. The empirical evidence is also consistent in its findings, with “overshifting” of these charges evident in all models since the 1980’s, i.e. $1 infrastructure charge results in greater than $1 increase in house prices. However, despite over a dozen separate studies over two decades in the US on this topic, no empirical works have been carried out in Australia to test if similar shifting or overshifting occurs here. The purpose of this research is to conduct a preliminary analysis of the more recent models used in these US empirical studies in order to identify the key study area selection criteria and success factors. The paper concludes that many of the study area selection criteria are implicit rather than explicit. By collecting data across the models, some implicit criteria become apparent, whilst others remain elusive. This data will inform future research on whether an existing model can be adopted or adapted for use in Australia.

History behind the IVF egg: Are women's comprehensive histories associated with the number of eggs collected, or fertilised normally, from repeated IVF cycles? [abstract]

Most studies of in vitro fertilisation (IVF) outcomes use cycle-based data and fail to account for women who use repeated IVF cycles. The objective of this study was to examine the association between the number of eggs collected (EC) and the percentage fertilised normally, and women’s self-reported medical, personal and social histories. This study involved a crosssectional survey of infertile women (aged 27-46 years) recruited from four privately-owned fertility clinics located in major cities of Australia. Regression modeling was used to estimate the mean EC and mean percentage of eggs fertilised normally: adjusted for age at EC. Appropriate statistical methods were used to take account of repeated IVF cycles by the same women. Among 121 participants who returned the survey and completed 286 IVF cycles, the mean age at EC was 35.2 years (SD 4.5). Women’s age at EC was strongly associated with the number of EC: <30 years, 11.7 EC; 30.0-< 35 years, 10.6 EC; 35.0-<40.0 years, 7.3 EC; 40.0+ years, 8.1 EC; p<.0001. Prolonged use of oral contraceptives was associated with lower numbers of EC: never used, 14.6 EC; 0-2 years, 11.7 EC; 3-5 years, 8.5 EC; 6þ years, 8.2 EC; p=.04. Polycystic ovary syndrome (PCOS) was associated with more EC: have PCOS, 11.5 EC; no, 8.3 EC; p=.01. Occupational exposures may be detrimental to normal fertilisation: professional roles, 58.8%; trade and service roles, 51.8%; manual and other roles, 63.3%; p=.02. In conclusion, women’s age remains the most significant characteristic associated with EC but not the percentage of eggs fertilised normally.