Micro-panel data with non-linear error components

该项目旨在开发具有异质边际效应和离散选择结果的面板数据模型方法，控制未观察到的共同因素和非线性误差成分;并应用这些方法分析澳大利亚的酒精引发的暴力和与毒品有关的伤害。该项目处于计量经济学进步的前沿，其成果有望扩大和深化澳大利亚的知识基础。经验性结果应当为预防犯罪的循证政策干预提供信息和评价，并影响有关公共交通和经济增长的政策制定。

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.