Business expectations and preferences regarding the introduction of daylight saving in Queensland

This paper examines the role of organisational, industry and regional characteristics in determining business support for the introduction of daylight saving in Queensland, Australia. The data employed is drawn from a survey of seven hundred and eight businesspersons in 2002 that assayed support for the statewide introduction of daylight saving in Queensland and an alternative policy where daylight saving would be restricted to the more urbanised southeast regions of Brisbane and/or the Gold Coast. Organisational characteristics examined include assessment of current and future business conditions, expectations of the impact of daylight saving on profits, sales, administration costs and staffing and the number of employees. Industry and region identifiers were also specified. Binary logit models are used to identify the source and magnitude of factors associated with business support for the introduction of daylight saving. The evidence provided suggests that support for the introduction of daylight saving is a function of positive expectations regarding staffing, sales and administration costs and is primarily associated with businesses providing electricity, gas, water and communications, finance and insurance and cultural and recreational services. There also appears to be strong rural and regional resistance to the introduction of daylight saving in Queensland, even among the business community.daylight saving time; organisational, industry and regional characteristics

Losing sleep at the market: An empirical note on the daylight saving anomaly in Australia

The ‘daylight saving effect’ predicts that the mean weekend return following the spring and fall/autumn changes in daylight saving time is less than the mean weekend return throughout the rest of the year. With this market anomaly, the change in market participants’ behaviour is linked with sleep desynchronosis and the change in circadian rhythm and its negative impact on sleep patterns. This study investigates the purported daylight saving effect in Australian equity market returns over the period 1979/80-2002/03 using parametric testing and regression analysis. After adjustments are made for heteroskedasticity and autocorrelation in the data, neither the transition to nor the movement from daylight saving is associated with returns that differ from other days. The results also show the absence of any significant weekend effect in the Australian equity market.Daylight saving time, daylight saving effect, weekend effect, market anomalies.

Emergency Funds in Australian Households: An Empirical Analysis of Capacity and Sources

This paper examines demographic and socioeconomic characteristics as predictors of emergency fund adequacy in Australian households. The results indicate that the presence of children, the number of dependents and income-earning units, the age and ethnicity of the household head, income dependency upon retirement plans and investments and government pensions and benefits, homeownership and disposable income are significant determinants of the capacity to raise emergency funds. They are also important predictors of the likely source of emergency funds. However, they are generally better at predicting mainstay sources of funds such as own savings and loans from deposit-taking institutions and credit card usage than loans from family or friends

AN EMPIRICAL SURVEY OF FRONTIER EFFICIENCY MEASUREMENT TECHNIQUES IN HEALTHCARE SERVICES

Healthcare institutions worldwide are increasingly the subject of analyses aimed at defining, measuring and improving organisational efficiency. However, despite the importance of efficiency measurement in healthcare services, it is only relatively recently that the more advanced econometric and mathematical frontier techniques have been applied to hospitals, nursing homes, health management organisations and physician practices. This paper attempts to provide a synoptic survey of the comparatively few empirical analyses of frontier efficiency measurement in healthcare services. Both the measurement of inefficiency in healthcare services and the determinants of healthcare efficiency are examined.data envelopment analysis; stochastic frontiers; technical, allocative and productive efficiency

Motor Vehicle Usage Patterns in Australia: A Comparative Analysis of Driver, Vehicle & Purpose Characteristics for Household & Freight Travel

An ordered probit model is used to predict motor vehicle usage in Australia on the basis of the unit record files underlying the Australian Bureau of Statistics’ Survey of Motor Vehicle Use. Both household and freight transport are analysed. The paper examines the statistical significance of a number of driver, vehicle and travel purpose variables on the level of motor vehicle usage. Factors analysed include driver age and gender, vehicle and fuel type, age of the vehicle, purpose of trip, place of registration, type of freight and number of drivers. The results indicate that the cut-off points between very low, low, medium, high and very high vehicle usages are significant and that the factors associated with differences in usage include driver age, engine size and age of vehicle for household vehicles and the type of freight, type of vehicle, gender and number of drivers for freight usage

Evaluating the Information Efficiency of Australian Electricity Spot Markets: Multiple Variance Ratio Tests of Random Walks

This paper examines whether Australian electricity spot prices follow a random walk. Daily peak and off-peak (base load) prices for New South Wales, Victoria, Queensland and South Australia are sampled over the period July 1999 to June 2001 and analysed using multiple variance ratio tests. The results indicate that the null hypothesis of a random walk can be rejected in all peak period and most off-period markets because of the autocorrelation of returns. For the Victorian market, the off-peak period electricity spot price follows a random walk. One implication of the study is that in most instances, stochastic autoregressive modelling techniques may be adequate for forecasting electricity prices

The Distribution of Financial Literacy in Australia

Ordered logit models are used to predict financial literacy on the basis of individual demographic, socioeconomic and financial characteristics. The data is drawn from the 2003 ANZ Survey of Adult Financial Literacy in Australia and relates to 3,548 respondents. Financial literacy is defined, amongst other things, in terms of standard mathematical ability and understanding of basic and advanced financial terms. Factors examined include gender, age, ethnicity, occupation, educational level and family structure, along with household income, savings (including superannuation), and mortgage and non-mortgage debt. The evidence suggests that financial literacy is highest for respondents aged between 50 and 60 years, professionals, executives, business and farm owners, and those who have completed university or college with higher levels of income, savings and debt. Financial literacy is lowest for females, the unemployed and other non-workers, those from a non-English speaking background, and those with only the lowest levels of secondary education. The models best predict the highest and lowest levels of financial literacy.Financial literacy; ordered logit; demographic, socioeconomic and financial characteristics.

Debt as a source of financial stress in Australian households

This paper examines the role of demographic, socioeconomic and debt portfolio characteristics as contributors to financial stress in Australian households. The data is drawn from the most-recent Household Expenditure Survey Confidentialised Unit Record Files (CURF) and relate to 3,268 probability-weighted households. Financial stress is defined, amongst other things, in terms of financial reasons for being unable to have a holiday, have meals with family and friends, and engage in hobbies and other leisure activities and overall financial management. Characteristics examined included family structure and composition, source and level of household income, age, sex and marital status, ethic background, housing value, debt repayments and credit card usage. Binary logit models are used to identify the source and magnitude of factors associated with financial stress. The evidence provided suggests that financial stress is higher in families with more children or other dependents and from ethnic minorities, especially those more reliant on government pensions and benefits, and negatively related to disposable income and housing value. There is little evidence to suggest that Australia’s historically high levels of household debt are currently the cause of significant amounts of financial stress in these households.Household and consumer debt, owner-occupied and investor housing, financial stress.

Emergency finance in Australian households An empirical analysis of capacity and sources

This paper examines demographic and socioeconomic characteristics as predictors of emergency finance in Australian households. The data is drawn from the most recent Household Expenditure Survey Confidentialised Unit Record Files (CURF) and relate to 6,892 probability-weighted households. Emergency finance is defined in terms of the ability to raise $2,000 within one week and its potential sources include own savings and loans from deposit-taking institutions, finance companies, credit cards, family and friends and welfare or community organisations. Characteristics examined included family structure and composition, source and level of household income, age, sex and marital status, ethnic background and housing value. Binary logistic models are used to identify the source and magnitude of factors associated with the ability to raise emergency finance and the likelihood of choosing each method of raising finance. The results indicate that the presence of children, the number of dependents and income-earning units, the age, sex and ethnicity of the household head, dependency upon government pensions and benefits, homeownership and disposable income are significant determinants of the capacity to raise emergency finance. However, the demographic and socioeconomic factors examined are generally better at predicting mainstay sources of finance such as own savings and loans from deposit-taking institutions and credit card usage than loans from family and friends and welfare or community organisations.Emergency funds, financial planning, economic and financial wellbeing.

Systematic Features of High-Frequency Volatility in Australian Electricity Markets: Intraday Patterns, Information Arrival and Calendar Effects

This paper investigates the intraday price volatility process in four Australian wholesale electricity markets; namely New South Wales, Queensland, South Australia and Victoria. The data set consists of half-hourly electricity prices and demand volumes over the period 1 January 2002 to 1 June 2003. A range of processes including GARCH, Risk Metrics, normal Asymmetric Power ARCH or APARCH, Student APARCH and skewed Student APARCH are used to model the timevarying variance in prices and the inclusion of news arrival as proxied by the contemporaneous volume of demand, time-of-day, day-of-week and month-of-year effects as exogenous explanatory variables. The skewed Student APARCH model, which takes account of right skewed and fat tailed characteristics, produces the best results in three of the markets with the Student APARCH model performing better in the fourth. The results indicate significant innovation spillovers (ARCH effects)and volatility spillovers (GARCH effects) in the conditional standard deviation equation, even with market and calendar effects included. Intraday prices also exhibit significant asymmetric responses of volatility to the flow of information