The use of injury surveillance databases to identify emerging injury hazards

Among the many valuable uses of injury surveillance is the potential to alert health authorities and societies in general to emerging injury trends, facilitating earlier development of prevention measures. Other than road safety, to date, few attempts to forecast injury data have been made, although forecasts have been made of other public health issues. This may in part be due to the complex pattern of variance displayed by injury data. The profile of many injury types displays seasonality and diurnal variance, as well as stochastic variance. The authors undertook development of a simple model to forecast injury into the near term. In recognition of the large numbers of possible predictions, the variable nature of injury profiles and the diversity of dependent variables, it became apparent that manual forecasting was impractical. Therefore, it was decided to evaluate a commercially available forecasting software package for prediction accuracy against actual data for a set of predictions. Injury data for a 4-year period (1996 to 1999) were extracted from the Victorian Emergency Minimum Dataset and were used to develop forecasts for the year 2000, for which data was also held. The forecasts for 2000 were compared to the actual data for 2000 by independent t-tests, and the standard errors of the predictions were modelled by stepwise hierarchical multiple regression using the independent variables of the standard deviation, seasonality, mean monthly frequency and slope of the base data (R = 0.93, R² = 0.86, F_{(3, 27)} = 55.2, p < 0.0001). Significant contributions to the model included the SD (β = 1.60, p < 0.001), mean monthly frequency (β =  - 0.72, p < 0.002), and the seasonality of the data (β = 0.16, p < 0.02). It was concluded that injury data could be reliably forecast and that commercial software was adequate for the task. Variance in the data was found to be the most important determinant of prediction accuracy. Importantly, automated forecasting may provide a vehicle for identifying emerging trends.

The relevance of demographic variables in assessing student satisfaction: a study of international postgraduate students

Servicing an increasingly diverse international student community in the globally competitive education market is a challenge faced by Australian universities. Market forecasts indicate a seven-fold increase in the number of students seeking higher education overseas by 2025 (Bohm et al, 2002) and with the growing diversity and competitiveness of the industry, universities will need to focus on factors influencing student satisfaction to improve service quality where required.

This paper, using logistic regression, ANOVA, and MANOVA, investigates the influence of country, age and gender with regard to satisfaction among international postgraduate students from four Asian countries studying in universities in Victoria. The results indicate that there is an inverse relationship between age and satisfaction among postgraduate students while the gender of the students does not have an impact on satisfaction, and that significant differences are evident between the four countries investigated with respect to the levels of satisfaction.

Student satisfaction : impact of age and gender on satisfaction among international postgraduate students from Asia

Customer satisfaction is a core-marketing concept. It is considered as a major outcome of marketing activity and serves to link processes, culminating in purchase and consumption with post-purchase phenomena such as attitudinal change, customer retention, repeat purchase, brand loyalty, positive word-of-mouth communication. Student satisfaction is a strategic factor in developing a competitive advantage in the highly attractive and globally competitive international education market. Market forecasts indicate a seven-fold increase in the number of students seeking higher education overseas by 2025 and given the competitiveness of the industry, universities will need to focus on variables influencing student satisfaction in order to address areas where improvements in service quality are required.

A sample of 371 postgraduate students from China, India, Indonesia and Thailand, is investigated. The study highlights the development of a scale to measure international postgraduate student satisfaction. The scale demonstrates the importance of four predominant factors influencing university choices - Education Resources; Communication and Guidance; Customer Value and Study Outcomes; and Image, Prestige and Recognition. Using logistic regression and chi square testing, this paper investigates the impact of age and gender on satisfaction among international postgraduate students from four Asian countries studying in universities in Victoria, Australia, on theses factors. The results indicate that age has a positive relationship with satisfaction among postgraduate students while the influence of gender has no effect on influencing satisfaction among postgraduate students from Asia.

International education services: challenges for Australia

Australian universities face a challenging task of servicing an increasingly diverse international student community in the globally competitive education market. The pressure on universities to successfully negotiate the cultural diversity and improvement in service quality will continue to increase with the global expansion of the international student market. Market forecasts indicate an increase in the number of students seeking higher education overseas by 2025 to 7.2 million. The attractiveness of the international education market in the form of both pecuniary and non pecuniary benefits will continue to create a highly competitive environment for Australia requiring Australian higher education institutions to pursue well planned strategies to maintain a globally competitive position.

Student satisfaction is a key strategic variable in maintaining such a competitive position with long term benefits arising from student loyalty, positive word of mouth (WOM) communication and image of the study destinations and to meet the challenges of increasing global competition, rising student expectations of quality, service and value for money.

This paper, based on the expectancy-disconfirmation paradigm, and using logistic regression, ANOVA and chi square testing, investigates factors that influence international postgraduate students from four Asian countries studying in Australia and concludes with strategic implications for universities

Contemporaneous intra-day volume, option, and futures volatility transmissions across parallel markets

The primary objective of this article is to investigate volatility transmission across three parallel markets operating on the Sydney Futures Exchange (SFE), both within and out of sample. Half-hourly observations are sampled from transaction data for the share price index (SPI) futures, SPI futures options, and 90-day bank accepted bill (BAB) futures markets, and the analysis is carried out using the simultaneous volatility (SVL) system of equations as well as competing volatility models. The results confirm the poor ability of GARCH models to fit intraday data. This study also applies an artificial nesting procedure to evaluate the out-of-sample volatility forecasts. Implied volatility has very limited (if any) predictive power when evaluated in isolation, whereas the SVL model with implied volatility embedded provides incremental information relative to competing model forecasts.

The exchange rate disconnect puzzle: a resolution?

Early empirical studies of exchange rate determinants demonstrated that fundamentals-based monetary models were unable to outperform the benchmark random walk model in out-of-sample forecasts while later papers found evidence in favor of long-run exchange rate predictability. More recent theoretical works have adopted a microeconomic structure; a utility-based new open economy macroeconomic framework and a rational expectations present value model. Some recent empirical work argues that if the models are adjusted for parameter instability, it is a good predictor of nominal exchange rates while others use aggregate idiosyncratic volatility to generate good predictions. This latest research supports the idea that fundamental economic variables are likely to influence exchange rates especially in the long run and further that the emphasis should change to the economic value or utility based value to assess these macroeconomic models.

Do retail option traders know better about market volatility?

This paper examines the informational content and predictive power of implied volatility over different forecasting horizons in a sample of European covered warrants traded in the Hong Kong and Singapore markets. The empirical results show that time-series-based volatility forecasts outperform implied volatility forecast as a predictor of future volatility. The finding also suggests that implied volatility is biased and informationally inefficient. The results are attributable to the fact in Hong Kong and Singapore the covered warrants markets are dominated by retail investors, who tend to use covered warrants' leverage to speculate on the price movements of the underlying rather than to express their view on volatility.

Forecasting inflation, industrial output and exchange rates : a template study for India

This paper reports results from a forecasting study for inflation, industrial output and exchange rates for India. We cannot reject the null hypothesis for linearity for all series used except for the growth rate of the foreign exchange series and our analysis is based on linear models, ARIMA and bivariate transfer functions and restricted VAR. Forecasting performance is evaluated using the models’ root mean-squared error differences and Theil’s inequality coefficients from recursive origin static, fixed origin dynamic and rolling origin dynamic forecasts. For models based on weekly data, based on RMSEs, we find that the bivariate models improve upon the forecasts of the ARIMA model while for models based on monthly data the ARIMA model has almost always better performance. In choosing between the two bivariate models on the basis of RMSEs, our overall results tend to support the use of a restricted VAR, as this model had the best forecasting performance more frequently than the transfer function model.

Monetary models of exchange rates and the random walk

Three alternative monetary models of exchange rate are tested using data on the Italian lira - US doIIar exchange rate. II is shown that up to the early 1990s these economic models perform better than the random walk model in out-of-sample forecasts.

Federally funded aged care provision in regional Victoria : Examining current provision and estimating future infrastructure requirements using existing population-based benchmarks

The following paper examines federally accredited and funded aged care provision in regional Victoria. Benchmarks that have been set by the Australian Department of Health and Ageing, are used to measure and compare the relative number of high and low level aged care positions and Community Aged Care Packages in six regional Victorian centres.
Using population forecasts, the additional aged care positions that each centre will require to meet the provision benchmarks in the year 2021 have been estimated. These figures are then translated into infrastructure requirements for the regional Victorian city of Greater Bendigo. This is done by surveying Greater Bendigo’s existing residential aged care facilities. Strategies for the provision of additional high and low level residential aged care infrastructure are explored using a matrix governed by size and configuration. Variations in these two aspects are shown to affect the location options for future facilities in Greater Bendigo. The implications of the benchmarks are also investigated in terms of facilities for the provision of Community Aged Care Packages.
The research is funded by a double ARC APAI grant between the Built Environment Research Group at Deakin University, The Centre for Sustainable Regional Centres at La Trobe University, the City of Greater Bendigo and the City of Warrnambool.

Forecasting industry-level CPI and PPI inflation : does exchange rate pass-through matter?

We show that incorporating the effects of exchange rate pass-through into a model can help in obtaining superior forecasts of domestic, industry-level inflation. Our analysis is based on a multivariate system of domestic inflation, import prices and exchange rates that incorporates restrictions from economic theory. These are restrictions on the transmission channels of the exchange rate pass-through to domestic prices, and are presented as testable hypotheses that lead to model reduction. We provide the results of various tests, including causality and prior restrictions, which support the underlying economic arguments and the model we use. The forecasting results for our model suggest that it has a superior performance overall, jointly producing more accurate forecasts of domestic inflation.

Do retail option traders know better about market volatility?

This paper examines the informational content and predictive power of implied volatility over different forecasting horizons in a sample of European covered warrants traded in the Hong Kong and Singapore markets. The empirical results show that time-series-based volatility forecasts outperform implied volatility forecast as predictors of future volatility. The finding also suggests that implied volatility is biased and informationally inefficient and that covered warrants are typically overvalued. The results are attributable to the fact that, in Hong Kong and Singapore, the covered warrants markets are dominated by retail investors who tend to use covered warrants' leverage to speculate on the price movements of the underlying assets rather than to express their view on volatility. Arbitrage is not possible in the markets as short-selling of covered warrants is prohibited.

The forecast quality of CBOE implied volatility indexes

We examine the forecast quality of Chicago Board Options Exchange (CBOE) implied volatility indexes based on the Nasdaq 100 and Standard and Poor's 100 and 500 stock indexes. We find that the forecast quality of CBOE implied volatilities for the S&P 100 (VXO) and S&P 500 (VIX) has improved since 1995. Implied volatilities for the Nasdaq 100 (VXN) appear to provide even higher quality forecasts of future volatility. We further find that attenuation biases induced by the econometric problem of errors in variables appear to have largely disappeared from CBOE volatility index data since 1995.

Forecasting stock index volatility : comparing implied volatility and the intraday high-low price range

The intraday high–low price range offers volatility forecasts similarly efficient to high-quality implied volatility indexes published by the Chicago Board Options Exchange (CBOE) for four stock market indexes: S&P 500, S&P 100, NASDAQ 100, and Dow Jones Industrials. Examination of in-sample and out-of-sample volatility forecasts reveals that neither implied volatility nor intraday high–low range volatility consistently outperforms the other.

The increasing importance of housing demography in the 21st century

To many, demography is an area which traditionally focuses upon macro issues such as migration and population forecasts. However traditional economic indicators cannot always observe the degree of purchaser and vendor willingness and therefore consideration should also be given to characteristics of buyers and sellers in the marketplace. This study draws the disciplines of housing research and demography closer and looks to social indicators for an insight into residential housing markets. This research analysed changes in the value of established residential house prices in Brisbane and the influence of variations in demographic variables on a dynamic time series basis. The results confirmed the existence of strong linkages between demographics and established house prices. While it is acknowledged that established house values are significantly influenced by external economic and political factors, this research confirmed that serious consideration must also be given to the increasing importance of housing demography