Prior sensitivity analysis for Bayesian Markov chain Monte Carlo output. This project aims to develop the first set of techniques to implement an automated output sensitivity analysis for Markov Chain Monte Carlo (MCMC) estimation methods. Computationally intense Bayesian MCMC provide a powerful alternative to classical methods for the estimation of economic models. An obstacle to their wider application is that researchers need to specify prior beliefs about model parameters that will affect t ....Prior sensitivity analysis for Bayesian Markov chain Monte Carlo output. This project aims to develop the first set of techniques to implement an automated output sensitivity analysis for Markov Chain Monte Carlo (MCMC) estimation methods. Computationally intense Bayesian MCMC provide a powerful alternative to classical methods for the estimation of economic models. An obstacle to their wider application is that researchers need to specify prior beliefs about model parameters that will affect the results. The expected outcomes will enable researchers to undertake a routine assessment of the sensitivity of the results to prior inputs.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
Discovery Early Career Researcher Award - Grant ID: DE150100309
Funder
Australian Research Council
Funding Amount
$328,614.00
Summary
Understanding the Dynamics of Socioeconomic Related Health Inequalities. Health differences across socio-economic groups have persisted in many countries, including Australia, despite decades of considerable improvements in life expectancy and average health status. Little is known of how policies may influence socio-economic health inequalities as the mechanisms underlying them are complex and the causes differ across population groups and over the lifecycle. This project aims to develop method ....Understanding the Dynamics of Socioeconomic Related Health Inequalities. Health differences across socio-economic groups have persisted in many countries, including Australia, despite decades of considerable improvements in life expectancy and average health status. Little is known of how policies may influence socio-economic health inequalities as the mechanisms underlying them are complex and the causes differ across population groups and over the lifecycle. This project aims to develop methods to quantify the major mechanisms that give rise to changes in socio-economic health inequalities in Australia. This project aims to improve our understanding of the dynamic factors that drive changes in health inequalities, thus providing useful information for decision makers about which policies will be cost effective at reducing them.Read moreRead less
Robust methods for heteroscedastic regression models for time series. What is the variability of the exchange rate of the Euro to the Australian dollar? Can the use of the electrocardiogram of a patient be improved as a diagnostic tool for heart disease? A well-known limitation of the existing statistical methods for answering these types of questions is that a small proportion of extreme observations have the potential to lead to results that are more in agreement with the outliers than with bu ....Robust methods for heteroscedastic regression models for time series. What is the variability of the exchange rate of the Euro to the Australian dollar? Can the use of the electrocardiogram of a patient be improved as a diagnostic tool for heart disease? A well-known limitation of the existing statistical methods for answering these types of questions is that a small proportion of extreme observations have the potential to lead to results that are more in agreement with the outliers than with bulk of the data. As a consequence, the statistical analyses may lead to wrong conclusions. This project aims to develop new methodologies to solve this problem for a large class of studies. Applications to stock market risk, exchange rate, and diagnosis of heart diseases will illustrate the new methods.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 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
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