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, including healthcare use data, and state-of-the-art econometric methods to generate causal evidence on these issues. Your work will produce insights directly relevant to labour-market policy, family services
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methods, including causal econometric analysis and predictive economic modelling, to assess the economic and distributional impacts of policy interventions across healthcare and disability service systems
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recently been awarded an Incorporating Patient Data in Health Technology Decision Making Grant under the 2025 Preventative and Public Health Research Initiative of the Medical Research Future Fund (MRFF
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aims to understand the supply-side drivers of patient fees for mental health services and their impact on socioeconomic inequities in access to care. It will use econometric methods and population-wide
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health economics, labour economics, economics and econometrics. We will also consider other quantitative disciplines such as data science, mathematical statistics, actuarial science or public health