Micro-Panel Data with Nonlinear Error Components: Advances and Applications

This project aims at (i) developing new methods for panel data models with heterogeneous marginal effects and discrete choice outcomes, controlling for unobserved common factors and nonlinear error components; (ii) applying the resulting methodologies to analyse alcohol-fuelled violence and drug-related harm in Australia. The proposed research lies at the forefront of current advances in econometrics and the outcomes will broaden/deepen Australia's knowledge base. Empirical outcomes will inform and evaluate evidence-based policy interventions for crime prevention, contributing to the Science and Research Priority area of Health. Outcomes will also influence policy making related to public transport and economic growth.