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 an additional degree leads to more than \$3000 (AUD, 2019) extra income 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 (HILDA). To take full advantage of the complexity and richness of this data we use a Machine Learning (ML) based methodology for causal effect estimation. 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:随着技术变革和自动化驱动许多职业所需技能的演变,晚年追求教育资格在OECD国家越来越普遍。我们关注晚年完成学位对经济回报的因果影响,因为获取额外教育的动机和能力可能与早年教育不同。我们发现,相比于没有完成额外学习的人,完成额外学位每年可带来超过3000澳元的额外收入(基准年份是2019年)。在处理和控制结果方面,我们使用了家庭收入和劳动力动态调查澳大利亚(HILDA)的极其丰富和具有全国代表性的纵向数据。为了充分利用此数据的复杂性和丰富性,我们使用了基于机器学习(ML)的方法进行因果效应估计。我们还能够使用ML来发现获得额外资格的影响的异质性来源。例如,获得额外资格时年龄小于45岁的人往往会获得更多好处(高达每周50澳元)。