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
New approaches for testing in nonlinear models. The outcome of this project is a new econometric methodology that will be particularly useful for developing our understanding of Australian (and global) financial markets. Specific benefits are that (i) our value-at-risk models will enhance national and international awareness of issues relating to financial risk management; (ii) our exchange rate pass through model will aid the development of Australian trade and pricing policies and (iii) our du ....New approaches for testing in nonlinear models. The outcome of this project is a new econometric methodology that will be particularly useful for developing our understanding of Australian (and global) financial markets. Specific benefits are that (i) our value-at-risk models will enhance national and international awareness of issues relating to financial risk management; (ii) our exchange rate pass through model will aid the development of Australian trade and pricing policies and (iii) our duration models for trade in Australian stocks will lead to a better understanding of the microstructure of the Australian stock market.Read moreRead less
Estimation and Inference in Weakly Identified Models. Economic and social systems are made up of interacting components leading to complex structures that are difficult to predict and manage. Consequently policy analysis and decision-making must be informed by statistical analysis of data. In many situations the informational content of observations is minimal; examples of such situations are found in the areas of education, health, finance and various aspects of macroeconomic analysis. This pro ....Estimation and Inference in Weakly Identified Models. Economic and social systems are made up of interacting components leading to complex structures that are difficult to predict and manage. Consequently policy analysis and decision-making must be informed by statistical analysis of data. In many situations the informational content of observations is minimal; examples of such situations are found in the areas of education, health, finance and various aspects of macroeconomic analysis. This project aims to develop methods of estimation and inference that make more efficient use of the information available in data. This will lead to more precise statistical analyses, resulting in a clearer understanding of economic and social systems, and better informed policy analysis and decision-making.Read moreRead less
A new look at modelling population heterogeneity in econometric study. This research will advance existing quantitative techniques in economic study. New theoretical results will help enhance Australian research reputations. The innovative techniques developed in this project will be demonstrated to study labour force participation of people with disabilities in Australia. Findings of the empirical study will help governments in providing financial assistance to affected families and addressing ....A new look at modelling population heterogeneity in econometric study. This research will advance existing quantitative techniques in economic study. New theoretical results will help enhance Australian research reputations. The innovative techniques developed in this project will be demonstrated to study labour force participation of people with disabilities in Australia. Findings of the empirical study will help governments in providing financial assistance to affected families and addressing the issue of labour shortage in Australia. Furthermore the participation of a high profile international researcher will benefit the local research community and provide a research training opportunity for local postgraduate students.Read moreRead less
A Multivariate Dynamic Factor Model of the Australian Business Cycle: Specification, Estimation and Empirical Results. The project aims to extend greatly existing models of national and international business cycles by developing a general class of dynamic factor models for Australia. The project provides a significant contribution to business cycle modelling by solving the intractability problems common to existing classes of dynamic factor models. A key innovation is the development of a simul ....A Multivariate Dynamic Factor Model of the Australian Business Cycle: Specification, Estimation and Empirical Results. The project aims to extend greatly existing models of national and international business cycles by developing a general class of dynamic factor models for Australia. The project provides a significant contribution to business cycle modelling by solving the intractability problems common to existing classes of dynamic factor models. A key innovation is the development of a simulation based estimator to circumvent the statistical and computational problems associated with existing estimators. The expected outcome of the project will be a more reliable way to monitor the phases of the cycle and forecast turning points, which will be of substantial national benefit.Read moreRead less
Persistence in Economic Time Series: Interpretation, Measurement and Inference. An economic time series is said to be persistent if shocks to the series have a permanent effect. Accurate and unambiguous inferences regarding persistence are crucial to an understanding of the response of the variable to shocks, in particular to policy-induced shocks. In this project we will explore new ways of interpreting, measuring and conducting inference on persistence. The aim is to produce significant theor ....Persistence in Economic Time Series: Interpretation, Measurement and Inference. An economic time series is said to be persistent if shocks to the series have a permanent effect. Accurate and unambiguous inferences regarding persistence are crucial to an understanding of the response of the variable to shocks, in particular to policy-induced shocks. In this project we will explore new ways of interpreting, measuring and conducting inference on persistence. The aim is to produce significant theoretical and methodological advances which, when applied to empirical problems, will enable reliable conclusions to be drawn regarding the propagation of shocks and, hence, the likely impact of interventionist government policies.Read moreRead less
Latent variable modelling of discrete choice experiments. Discrete choice experiments and models are used to forecast consumer responses to changes in products policies and programs worldwide. Recent research suggests key model assumptions are violated because error variances covary with observed and unobserved factors. In order to address this, we will model systematic relationships between error variances and observed (eg, prices, survey length) and unobserved (eg, 'convenience', 'reputation') ....Latent variable modelling of discrete choice experiments. Discrete choice experiments and models are used to forecast consumer responses to changes in products policies and programs worldwide. Recent research suggests key model assumptions are violated because error variances covary with observed and unobserved factors. In order to address this, we will model systematic relationships between error variances and observed (eg, prices, survey length) and unobserved (eg, 'convenience', 'reputation') factors to improve model reliability and accuracy. This should lead to more accurate models/forecasts, benefitting business and government, which addresses the national priority of 'frontier technologies, promoting an innovative culture and economy'.Read moreRead less
Threshold models in micro-econometrics with applications to empirical models of health. The aim of this project is to develop and apply new statistical approaches to endogenously identify non-linear relationships between explanatory variable(s) and the response variable in non-linear econometric models and to illustrate these with applications important to empirical health economics. Literature proliferates in linear models with non-linear effects, but in health economics non-linear models domin ....Threshold models in micro-econometrics with applications to empirical models of health. The aim of this project is to develop and apply new statistical approaches to endogenously identify non-linear relationships between explanatory variable(s) and the response variable in non-linear econometric models and to illustrate these with applications important to empirical health economics. Literature proliferates in linear models with non-linear effects, but in health economics non-linear models dominate. This project will generalise these techniques to allow for various forms of the threshold variable(s), including categorical and continuous, endogenous and exogenous, and those measured with error.Read moreRead less
Modelling health: Reporting behaviour and misclassification using survey data. Empirical models based on large scale survey data sets are used by health economists to inform policymakers. However, in the case of sensitive topics, a potential for survey misreporting may lead to inaccurate estimates of aberrant behaviours. To date, little work has been done analysing the extent and consequences of inaccurate reporting, especially within health economics. By addressing areas where potential for mis ....Modelling health: Reporting behaviour and misclassification using survey data. Empirical models based on large scale survey data sets are used by health economists to inform policymakers. However, in the case of sensitive topics, a potential for survey misreporting may lead to inaccurate estimates of aberrant behaviours. To date, little work has been done analysing the extent and consequences of inaccurate reporting, especially within health economics. By addressing areas where potential for misinformation is high, the overall quality of results will be enhanced. This research will be submitted to highly ranked health economics and econometrics journals to be made available to relevant policymakers intent on ensuring a healthy society.Read moreRead less