Bayesian analysis of individual decisions in health and labour economics

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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.