Pursuing educational qualifications later in life is an increasingly common phenomenon within OECD countries since technological change and automation continues to drive the evolution of skills needed in many professions. We focus on the causal impacts to economic returns of degrees completed later in life, where motivations and capabilities to acquire additional education may be distinct from education in early years. We find that completing and additional degree leads to more than \$3000 (AUD, 2019) per year compared to those who do not complete additional study. For outcomes, treatment and controls we use the extremely rich and nationally representative longitudinal data from the Household Income and Labour Dynamics Australia survey is used for this work. To take full advantage of the complexity and richness of this data we use a Machine Learning (ML) based methodology to estimate the causal effect. We are also able to use ML to discover sources of heterogeneity in the effects of gaining additional qualifications, for example those younger than 45 years of age when obtaining additional qualifications tend to reap more benefits (as much as \$50 per week more) than others.

翻译：在经合组织国家中，随着技术变革和自动化持续推动众多职业所需技能的演进，人生晚期追求教育资格已成为日益普遍的现象。本研究聚焦于晚年完成学位对经济回报的因果影响——在此阶段，个体获取额外教育的动机与能力可能显著区别于早年求学时期。研究发现，相较于未完成额外学习者，完成额外学位者年均收入增加逾3000澳元（2019年澳元现值）。本研究基于澳大利亚家庭收入与劳动力动态调查中极具丰富性的全国代表性纵向数据，构建结果变量、处理组与对照组。为充分挖掘该复杂数据的深层价值，我们采用基于机器学习的方法论进行因果效应估计，并借助该技术发现获得额外资质效应的异质性来源——例如，45岁以下获得额外资质者每周收益较其他群体高出50澳元。