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Field of Research : Health Economics
Field of Research : Econometric and Statistical Methods
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  • Researchers (14)
  • Funded Activities (11)
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  • Funded Activity

    Discovery Projects - Grant ID: DP110102721

    Funder
    Australian Research Council
    Funding Amount
    $470,574.00
    Summary
    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.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP170103135

    Funder
    Australian Research Council
    Funding Amount
    $379,500.00
    Summary
    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.
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    Active Funded Activity

    ARC Future Fellowships - Grant ID: FT170100124

    Funder
    Australian Research Council
    Funding Amount
    $802,000.00
    Summary
    Bayesian analysis of individual decisions in health and labour economics. This project aims to exploit emerging Bayesian Markov chain Monte Carlo methods to develop new approaches to modelling economic decision making. These methods will generate insights into two current and important policy debates. This includes (i) marijuana, alcohol and tobacco use and legalisation of marijuana use; and (ii) parental leave policies, maternity leave decisions and mothers' labour market dynamics. Although p .... Bayesian analysis of individual decisions in health and labour economics. This project aims to exploit emerging Bayesian Markov chain Monte Carlo methods to develop new approaches to modelling economic decision making. These methods will generate insights into two current and important policy debates. This includes (i) marijuana, alcohol and tobacco use and legalisation of marijuana use; and (ii) parental leave policies, maternity leave decisions and mothers' labour market dynamics. Although policies play an important role in observed health and labour market behaviours, their exact effects on individuals' decisions and outcomes are often difficult to quantify due to the complex nature of the decision process. Outcomes from the project will include new evidence of changes in substance uses under different legal scenarios and provide benefits such as yielding vital evidence on labour market and health behaviour impacts to support policy makers and strengthen Australia's research capacity in Bayesian analysis.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP220103306

    Funder
    Australian Research Council
    Funding Amount
    $220,602.00
    Summary
    Physician Preferences for Medical Innovation. This project aims to identify the causes and consequences of medical practice variations by providing new evidence on the process through which physicians adopt and use new medical technology. This project expects to generate new knowledge on how physicians' human and social capital determine their preferences for taking up new medical technology and the economic consequences of such decisions. Expected outcomes of this project include a greater unde .... Physician Preferences for Medical Innovation. This project aims to identify the causes and consequences of medical practice variations by providing new evidence on the process through which physicians adopt and use new medical technology. This project expects to generate new knowledge on how physicians' human and social capital determine their preferences for taking up new medical technology and the economic consequences of such decisions. Expected outcomes of this project include a greater understanding of the sources for and costs of inappropriate use of healthcare, such as low-value care. This should provide significant benefits, such as contributing to the construction of effective policies for improving efficiency and equity of the healthcare system.
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    Funded Activity

    Australian Laureate Fellowships - Grant ID: FL110100247

    Funder
    Australian Research Council
    Funding Amount
    $2,461,000.00
    Summary
    Understanding the implications of population ageing for the future costs of funding health care, aged care and aged pensions in Australia. Decisions about health insurance, aged care, superannuation and retirement are often very complex, and most people find making the best choices extremely challenging. This project will develop new models and design new policies that can help people make better decisions in these areas, leading to greater well being in retirement.
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    Funded Activity

    Discovery Projects - Grant ID: DP140100748

    Funder
    Australian Research Council
    Funding Amount
    $350,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP140100743

    Funder
    Australian Research Council
    Funding Amount
    $341,000.00
    Summary
    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.
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    Funded Activity

    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.
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    Active Funded Activity

    ARC Future Fellowships - Grant ID: FT170100401

    Funder
    Australian Research Council
    Funding Amount
    $944,000.00
    Summary
    Improving productivity: theory and application to Australian hospitals. This project aims to improve existing methods for analysing productivity and efficiency of organisations. The new methods will be applied to Australian hospitals, to analyse their productivity and efficiency, identify the best-practices and their determinants and recommend improvements and necessary reforms. The high level of healthcare costs in Australia, about 5 percent of gross domestic product, as well as their rapid and .... Improving productivity: theory and application to Australian hospitals. This project aims to improve existing methods for analysing productivity and efficiency of organisations. The new methods will be applied to Australian hospitals, to analyse their productivity and efficiency, identify the best-practices and their determinants and recommend improvements and necessary reforms. The high level of healthcare costs in Australia, about 5 percent of gross domestic product, as well as their rapid and accelerating growth, imply that application of methods developed through this project may save billions of dollars and, more importantly, thousands of lives. An expected outcome of this project will be superior theoretical and practical methods for analysing productivity and efficiency of economic systems, to enhance understanding of the potential for improvements and of the necessary reforms.
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    Funded Activity

    Discovery Projects - Grant ID: DP150104630

    Funder
    Australian Research Council
    Funding Amount
    $333,581.00
    Summary
    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.
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