A cohort analysis of the demand for meat and the impact of food scares. Australia is the largest beef exporter in the world. In 1999, there were 22.7 million beef cattle, producing 2 million tonnes with a gross value of $4.4 million. To date, Australia has been unaffected by the growing number of major health scares currently plaguing many European and South American countries. Equivalent scares in Australia would be devastating and hence research into the impact of scares on the behaviour of co ....A cohort analysis of the demand for meat and the impact of food scares. Australia is the largest beef exporter in the world. In 1999, there were 22.7 million beef cattle, producing 2 million tonnes with a gross value of $4.4 million. To date, Australia has been unaffected by the growing number of major health scares currently plaguing many European and South American countries. Equivalent scares in Australia would be devastating and hence research into the impact of scares on the behaviour of consumers is of paramount importance. It is the purpose of this research project to quantify the effects of such health/product scares on the demand for meat.
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Identification and inference in nonparametric models. This project will develop reliable methods for identification, estimation and inference of nonparametric models for the evaluation of economic policies on outcome variables of interest. This econometric methodology will allow a better understanding of the quantitative effects of an economic policy which will result in better informed policy decisions. The results will have applications to labour market policies, health care policies and educa ....Identification and inference in nonparametric models. This project will develop reliable methods for identification, estimation and inference of nonparametric models for the evaluation of economic policies on outcome variables of interest. This econometric methodology will allow a better understanding of the quantitative effects of an economic policy which will result in better informed policy decisions. The results will have applications to labour market policies, health care policies and education policies among others. The project will also provide national benefits in terms of building up the local stock of researchers trained in the area of identification and estimation of nonparametric models; it will further improve the international reputation that Australia has in econometric theory.Read moreRead less
Distributional Consequences of Mass-Market Higher Education in Business. Increased access to tertiary education has not been evaluated for its effects on the full spectrum of individuals served by the tertiary sector. Using longitudinal data on entire student populations at university business faculties, this project will provide the first Australian evidence on the trade-offs amongst the educational success of students with different levels of preparation that occur when those with poorer prep ....Distributional Consequences of Mass-Market Higher Education in Business. Increased access to tertiary education has not been evaluated for its effects on the full spectrum of individuals served by the tertiary sector. Using longitudinal data on entire student populations at university business faculties, this project will provide the first Australian evidence on the trade-offs amongst the educational success of students with different levels of preparation that occur when those with poorer preparation are added to classrooms. Short-term performance and medium-term attrition, a recent educational policy focus, will be evaluated. Theoretically grounded recommendations will result for undergraduate program design to suit a student population with varying levels of university preparation.Read moreRead less
Bayesian choice modelling. Discrete choice models are important as they provide tools to help understand choice processes of decision makers. It remains a challenge to specify models with covariance structures flexible enough to capture complex patterns of cross-substitution between choices while being able to capture heterogeneity present in individual behaviour. We will develop a Bayesian approach to choice modelling that uses covariance selection to overcome these problems. This will train re ....Bayesian choice modelling. Discrete choice models are important as they provide tools to help understand choice processes of decision makers. It remains a challenge to specify models with covariance structures flexible enough to capture complex patterns of cross-substitution between choices while being able to capture heterogeneity present in individual behaviour. We will develop a Bayesian approach to choice modelling that uses covariance selection to overcome these problems. This will train researchers and raise the profile of Australia in an active research area that is important in the social sciences; substantive applications will be in health economics, but developments will also be relevant to cognate areas of biostatistics, epidemiology, and ecology.Read moreRead less
Nonlinear spatial and spatiotemporal econometrics: theory with applications. Modern societies like Australia have major challenges in the forecasting, measuring and managing of risks associated with global economic and environmental/climate changes. These tasks require advanced econometric techniques in modelling and forecasting of complex nonlinear spatiotemporal variability in economic and social systems. This project will develop frontier econometric technologies that enable more accurate eco ....Nonlinear spatial and spatiotemporal econometrics: theory with applications. Modern societies like Australia have major challenges in the forecasting, measuring and managing of risks associated with global economic and environmental/climate changes. These tasks require advanced econometric techniques in modelling and forecasting of complex nonlinear spatiotemporal variability in economic and social systems. This project will develop frontier econometric technologies that enable more accurate economic and climate forecasts. The tools produced will provide Australia's scientists and policy-makers with a greater capacity to manage the risks associated with these challenges. A side-benefit of the research will be high-quality publications that enhance the nation's reputation in this cutting edge research.Read moreRead less
Robust Productivity Measurement: An Econometric Distance Function Approach. Accurate measures of productivity are required in a range of economic analyses. For example, in the assessment of the success of microeconomic reforms, or in price-cap regulation of utility and transport infrastructure firms. In this project we investigate the use of econometric distance functions as a means of obtaining improved productivity measures. This new approach addresses the main criticisms of alternative ap ....Robust Productivity Measurement: An Econometric Distance Function Approach. Accurate measures of productivity are required in a range of economic analyses. For example, in the assessment of the success of microeconomic reforms, or in price-cap regulation of utility and transport infrastructure firms. In this project we investigate the use of econometric distance functions as a means of obtaining improved productivity measures. This new approach addresses the main criticisms of alternative approaches, such as the single output restriction in the production function approach, the optimisation assumptions embedded in both the value dual approach and the Törnqvist index approach, and the statistical noise criticism of the data envelopment analysis approach.Read moreRead less
Effects of Maternal Work, Day Care Use and Other Investments in Children on Child Cognitive Outcomes. Later life outcomes due to investments by individuals and/or society in children is crucial to many countries, including Australia. Appropriate policy responses require reliable and valid estimates of the likely effects of individual investments and policy interventions. Despite many research reports on this topic, almost all do not control for selection bias (eg, high achieving mothers tend to ....Effects of Maternal Work, Day Care Use and Other Investments in Children on Child Cognitive Outcomes. Later life outcomes due to investments by individuals and/or society in children is crucial to many countries, including Australia. Appropriate policy responses require reliable and valid estimates of the likely effects of individual investments and policy interventions. Despite many research reports on this topic, almost all do not control for selection bias (eg, high achieving mothers tend to put children in day care), which is a feature of our work. Thus, our empirical results will have major policy implications, and will suggest ways to obtain similar results for Australian environments. Read moreRead less
Efficient pooling of cross-section and time series data using Bayesian machine learning with two econometric applications. In this project, we adapt a Bayesian modelling strategy, namely the minimum message length principle, to the problem of efficient partitioning of economic units, such as firms or countries, into groups whose behavioural patterns are similar within each group but distinct across groups. This methodology can incorporate the requirements of economic theory. The resulting softwa ....Efficient pooling of cross-section and time series data using Bayesian machine learning with two econometric applications. In this project, we adapt a Bayesian modelling strategy, namely the minimum message length principle, to the problem of efficient partitioning of economic units, such as firms or countries, into groups whose behavioural patterns are similar within each group but distinct across groups. This methodology can incorporate the requirements of economic theory. The resulting software will be developed for the Web. We consider two specific applications, namely modelling gasoline demand in OECD countries, and finding the foreign factor with the most predictive power for the growth rate of the Australian economy. The second application is of considerable national interest.Read moreRead less
Efficient Estimation of Statistical Models with Many Parameters. Statistical models are used extensively in business, engineering and the sciences to describe the behavior of systems subject to uncertainty. There are often many unknowns in such models and relatively little data to estimate them. The object of the research is to develop methods that make these statistical models practical to use. The research team will apply the methodology to solve problems in economics, finance, marketing and t ....Efficient Estimation of Statistical Models with Many Parameters. Statistical models are used extensively in business, engineering and the sciences to describe the behavior of systems subject to uncertainty. There are often many unknowns in such models and relatively little data to estimate them. The object of the research is to develop methods that make these statistical models practical to use. The research team will apply the methodology to solve problems in economics, finance, marketing and the analysis of gene expression data. The project will also train doctoral and postdoctoral students and enhance Australia's reputation for research excellence in the Statistical and Mathematical Sciences. Read moreRead less
Bayesian estimation of flexible spatial models with applications in medical imaging and econometric modeling. This project aims to develop statistical methodology for estimating flexible highly parameterised Bayesian spatial models. The flexible models examined will include regression, choice and time series models for data that is spatially registered. Spatial smoothing of parameters in the models will involve application of hierarchical spatial prior distributions. The resulting methodology wi ....Bayesian estimation of flexible spatial models with applications in medical imaging and econometric modeling. This project aims to develop statistical methodology for estimating flexible highly parameterised Bayesian spatial models. The flexible models examined will include regression, choice and time series models for data that is spatially registered. Spatial smoothing of parameters in the models will involve application of hierarchical spatial prior distributions. The resulting methodology will be applied to the analysis of medical imaging data and to the estimation of spatial econometric models of residential real estate prices. The expected outcomes include developments in the frontier framework of Bayesian computational estimation methodology, improved methods for medical image processing and estimation of high resolution spatial models of residential real estate prices in Australian metropolitan centres.Read moreRead less