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OECD国家中,晚年追求教育资格是一个日益普遍的现象,因为技术变革和自动化正在推动许多专业所需技能的演变。本文重点研究晚年完成学位对经济回报的因果影响,在这种情况下,获得额外教育的动机和能力可能与早年教育有所不同。我们发现,与那些不进行额外学习的人相比,完成额外学位可带来每年超过3000澳元的回报(2019 AUD)。我们使用“Household Income and Labour Dynamics Australia survey”这一极其丰富且具有代表性的纵向数据来进行研究。为了充分利用这个数据的复杂性和丰富性,我们使用了基于机器学习的方法来估计因果效应。我们还能够使用机器学习来发现获得额外资格的效应异质性的来源,例如年龄在45岁以下获得额外资格的人 tend 比其他人在经济效益上获得更多的好处(多达每周50澳元)。