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Field of Research : Econometrics
Socio-Economic Objective : Preference, Behaviour and Welfare
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  • Active Funded Activity

    ARC Future Fellowships - Grant ID: FT180100632

    Funder
    Australian Research Council
    Funding Amount
    $857,585.00
    Summary
    Solving and estimating dynamic models of strategic interaction. This project aims to investigate how firms interact with each other through time and how these interactions drive both the operation of, and value created in, economic markets. While recent theoretical models predominantly capture the complexity of these dynamic interactions, the methods for testing these models’ predictions against observed data do not. Instead, they are based on a range of simplifying assumptions that undermine th .... Solving and estimating dynamic models of strategic interaction. This project aims to investigate how firms interact with each other through time and how these interactions drive both the operation of, and value created in, economic markets. While recent theoretical models predominantly capture the complexity of these dynamic interactions, the methods for testing these models’ predictions against observed data do not. Instead, they are based on a range of simplifying assumptions that undermine the reliability of their analysis. This project will develop statistical and computational methods to better understand observed economic behaviour. By allowing the effects of proposed economic interventions and regulations ex ante, this project will support the development of more efficient and better-targeted policies in every area of the economy.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE120100748

    Funder
    Australian Research Council
    Funding Amount
    $375,000.00
    Summary
    Robust inference for behavioural models in economics and finance. The project will develop novel methodology to estimate behavioural models in economics and finance, which may give better insights on economic development. Knowledge gained from this project will be useful for Australian industries, banks, investment funds and the government for the effective formulation of their business strategies and policies.
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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 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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    Showing 1-4 of 4 Funded Activites

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