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
An econometric analysis of the impact of education on health in developing countries. This project will provide empirical knowledge on whether education affects health over the life course in developing countries. This research will aid the design of more cost effective strategies aiming to reduce poverty and promote economic development, which will ultimately lead to a more prosperous and safe region and world.
Flexible methods for latent variable models applied to Health Economics. This project aims to develop flexible and powerful methods for estimating models containing variables that are unobserved, that is, latent. Such models are often used to capture individual heterogeneity and time dependence in data collected on individuals, with each individual observed for several time periods. Latent variables can also infer group membership, where such membership is unavailable from the data. The intended ....Flexible methods for latent variable models applied to Health Economics. This project aims to develop flexible and powerful methods for estimating models containing variables that are unobserved, that is, latent. Such models are often used to capture individual heterogeneity and time dependence in data collected on individuals, with each individual observed for several time periods. Latent variables can also infer group membership, where such membership is unavailable from the data. The intended methodology is Bayesian and based on new particle methods that allow users to select between models and predict future observations even in complex situations. The research aims to inform decision making through improved use of data in health economics and related fields.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170100644
Funder
Australian Research Council
Funding Amount
$371,000.00
Summary
Nonlinear econometric panel models with fixed effects. This project aims to develop effective quantitative methods tailored to policy questions in public health and international trade. Many nonlinear panel models are essential to answer policy-relevant research questions, but cannot estimate key objects of interest, while default procedures for inference are often misleading, making magnitudes of identified effects impossible to quantify. This project will develop methods to overcome these limi ....Nonlinear econometric panel models with fixed effects. This project aims to develop effective quantitative methods tailored to policy questions in public health and international trade. Many nonlinear panel models are essential to answer policy-relevant research questions, but cannot estimate key objects of interest, while default procedures for inference are often misleading, making magnitudes of identified effects impossible to quantify. This project will develop methods to overcome these limitations for many econometric models, and apply them to important models in health economics and international trade. Such improvements are expected to reduce risk in public decision-making, resulting in better and more effective policies.Read moreRead less
Micro-panel data with non-linear error components. This project aims to develop methods for panel data models with heterogeneous marginal effects and discrete choice outcomes, controlling for unobserved common factors and nonlinear error components; and apply the methodologies to analyse alcohol-fuelled violence and drug-related harm in Australia. The project lies at the forefront of advances in econometrics, and the outcomes are expected to broaden and deepen Australia’s knowledge base. Empiric ....Micro-panel data with non-linear error components. This project aims to develop methods for panel data models with heterogeneous marginal effects and discrete choice outcomes, controlling for unobserved common factors and nonlinear error components; and apply the methodologies to analyse alcohol-fuelled violence and drug-related harm in Australia. The project lies at the forefront of advances in econometrics, and the outcomes are expected to broaden and deepen Australia’s knowledge base. Empirical outcomes should inform and evaluate evidence-based policy interventions for crime prevention, and influence policy making about public transport and economic growth.Read moreRead less