Prototype Statistics on Employment Outcomes of Tertiary Education presents prototype statistics from the integrated Employment Outcomes of Tertiary Education (EOTE) data, which links administrative tertiary education data with data on employers and employees. These statistics show that reliable official statistics can be produced from such a dataset because:
- Collectively, the input datasets are of sufficiently high quality to enable official statistics to be produced from the integrated data.
- The input datasets can be linked to create an integrated dataset that is of sufficiently quality to produce official statistics.
- From this integrated dataset it is possible to produce statistics that provide a relatively simple but coherent overview of the future employment and earnings experiences of recent participants in tertiary education. The institution-based statistics provide more comprehensive coverage than the student loans and allowances release, which contains information on post-study earnings experiences for students with student loans and/or allowances only. Examples of the statistics available from the EOTE dataset are presented in this report.
It is also important to acknowledge the following:
- While the input datasets are generally of high quality, there is a need to further develop understanding of the data. The knowledge of the industry training and National Qualification Framework (NQF) data is less developed than that of institution-based Tertiary Student Enrolments and Completions (TSEC) data.
- Official statistics could only be produced for individuals who participated in tertiary education and training from 2003 onwards. Data limitations and low match rates preclude earlier statistics.
- While the prototype statistics are relatively simple, interpretation of the information is not. These prototype statistics describe the population’s employment and earnings experiences. However, determining the extent to which labour market experiences are attributable to tertiary education and training is difficult, as previous education, work experience, and age, all influence employment and earnings. We consider this to be beyond the scope of the statistical outputs and better served by more specialised research.
This paper concludes with potential areas for further work. To help inform this, Statistics NZ welcomes the comments of stakeholders and potential data users.