The CSO is committed to broadening the range of high-quality information it provides on societal and economic change. The large increase in the volume and nature of secondary data in recent years poses a variety of challenges and opportunities for institutes of national statistics. Joining secondary data sources in a safe manner across public service bodies, while adhering to statistical and data protection legislation, can provide new analysis and outputs to support decision-making and accountability in a way that is not possible using discrete datasets. Furthermore, a coordinated approach to data integration can lead to cost savings, greater efficiency and a reduction in duplication.
The CSO has a formal role in coordinating the integration of statistical and administrative data across public service bodies that together make up the Irish Statistical System (ISS). Underpinning this integration is the development of a National Data Infrastructure (NDI) – a platform for linking data across the administrative system using unique identifiers for individuals, businesses and locations. The data linking for statistical purposes is carried out by the CSO on pseudonymised datasets using only those variables which are relevant to the research being undertaken. A strong focus on data integration, which requires the collection and storage of identifiers such as PPSN and Eircodes, is a priority of the ISS in its goal of improving the analytical capacity of the system.
Data protection is a core principle of the CSO and is central to the development of the NDI. As well as the strict legal protections set out in the Statistics Act, 1993, and other existing regulations, we are committed to ensuring compliance with all data protection requirements. These include the Data Sharing and Governance Act (2019) and the General Data Protection Regulation (GDPR, EU 2016/679).
The analysis in this report uses the Post-Primary Online Database (PPOD) as its primary source. This contains details on student progression, including programme type, programme year, and demographics such as age and sex. It examines outcomes for students last appearing in the PPOD’s 2011/2012 and 2012/2013 academic years.
The cohorts are the Leaving Certificate Examination (LCE) Completers and Early Leavers. Students are considered to have completed the Leaving Certificate programme if they enrolled in the Leaving Certificate programme Year 2 and were not recorded as having left post-primary education early.
Early Leavers were those who were either enrolled in Leaving Certificate programme year one and did not enrol in year two, or were recorded as an early leaver in their LC programme year two PPOD entry.
Excluded Categories of Students
Educational outcomes from non-HEA designated institutions (i.e. private and independent colleges) are not covered in this analysis. A report for the Expert Group on Future Skills Needs indicated that in 2014 there were approximately 5,000 higher education awards made to learners outside the HEA higher education sector. There are a growing number of private and independent colleges in Ireland. Some of the larger institutions include Griffith College, King’s Inns, National College of Ireland, Dublin Business School, Galway Business School, Independent College Dublin, Hibernia College, and a number of others in areas such as business, law, computing, music and psychotherapy/counselling. There was a number of other further education courses not accredited by QQI, such as City & Guilds courses, which are also excluded from this analysis.
A number of pupil records have a missing or invalid PPSN, and therefore these cannot be matched to other administrative data sources. The rates of missing and invalid PPSN across a number of parameters are given in the chapter on Background Statistics. This is given as a guide to the user and may be used to develop a clearer picture of the quality of the data and composition of the various groups.
Academic years and outcome years
The year of Leaving Certificate completion is the latter of the two calendar years spanned by the final academic year. For example, where a students’ final academic year was 2012/2013, the completion year is taken as 2013. The first year outcome then refers to the same calendar year, as many students would subsequently enrol in higher or further education at that point.
The Irish National Framework for Qualifications (NFQ) is a framework which classifies learning achievement based on the level of knowledge, skill and competence. 'Award type' in this report refers to names that are commonly given to different types of qualifications, such as certificate, higher honours bachelor’s degree, master’s degree, etc. For the most part, NFQ Level 6 awards are advanced certificates or higher certificates, Level 7 awards are primarily ordinary bachelor’s degrees and Level 8 awards are primarily higher honours bachelor’s degrees. Level 9 awards include master’s degrees and postgraduate diplomas. Level 10 awards are doctoral degrees (Ph.D., including higher doctorates). The relationship between award type and NFQ Level is not precisely one-to-one, however. NFQ level is used as an analysis variable throughout this report since it is fully standardised.
Field of study
The fields of study referred to in this report are based on the International Standard Classification of Education (ISCED) broad fields. Due to a change in the ISCED classification framework in 2013, some mapping was used to assign equivalent broad field classifications to courses from years prior to 2014. This mapping is described in the ELD methodology documentation.
An individual is regarded as being 'in substantial employment' within a given calendar year if they fulfil either of the criteria A or B below.
A. Substantial P35 Employment - They fulfill the following two requirements:
B. Substantial Self-Employment - Their total turnover across all self-employment activities is at least €1,000 within the calendar year.
Enrolled in Education and Training
Enrolment in education and training after completing or exiting the Leaving Certificate programme was analysed using records from
If a student was enrolled in an educational outcome, they were counted as active in that outcome for the appropriate adjacent years, given that most educational activity runs from September of any given year to the following spring. For PPOD re-enrolments and HEA enrolments, activity is counted for the enrolment year and one year forward from the administrative record. For further education based on QQI awards, activity is counted for the award year and one year prior to the award.
Youthreach is an important outcome for this study. It caters to early school-leavers to ensure they continue to engage with education. While headline figures for Youthreach are available from the Department of Education and Skills for the years 2012 - 2017, there is no granular administrative data available prior to 2017. Sufficient data is subsequently available from the Programme Learner Support System (PLSS) for 2017.
To estimate Youthreach enrolments for the outcome years 2012-2017, the rates of Personal Identifier Key (PIK) matching between the PPOD and Youthreach in 2017 were applied to the early-school leaver numbers from the academic years 2011/2012 – 2017/2018. Figure 10.1 below illustrates when 2017 Youthreach enrolees were last enrolled on the PPOD. Up to 49.8% of the 2,990 Youthreach enrolments in 2017 were early school-leavers from the academic years 2011/2012 – 2017/2018.
|Years since last post-primary enrolment|
In 2017, 14.2% of Youthreach enrolments were last enrolled in post-primary in the same academic year 2017/2018, while 6.8% were last enrolled in post-primary in the 2016/2017 academic year. This distribution is applied to the overall Youthreach numbers for 2012 – 2017 (as presented in table 10.1), to estimate Youthreach as an outcome for the 2011/2012 cohort (and subsequently the 2012/2013 cohort).
|Table 10.1 Total Youthreach enrolments by academic year|
Applying the percentages illustrated in Figure 10.1 to the relevant outcome years produces the estimates for Youthreach found in Chapter 4 - Education & Training, which feed into the overall education and training numbers throughout the report.
Neither Education nor Employment
Where a student was neither 'in substantial employment', or enrolled in education within a specific calendar year, but their PIK appeared in Department of Social Protection records as receiving a State payment, or it appeared in Revenue records but did not achieve the threshold for substantial employment, they were classified as in neither education nor employment.
The following is a list of examples of situations where a student would fall into this category:
A student is assigned to the category of ‘not captured' if they do not appear in any of the datasets used in this analysis for that year and have no recorded activities such as those listed above. This categorisation includes elements of international migration and enrolment in private educational institutions for which no administrative data is available.
The Statistical Classification of Economic Activities in the European Community, normally known simply as NACE, is a classification system used to describe industry sectors in the European Union. Employers in the P35 database are assigned a NACE code based on their main activity. Graduates who demonstrate substantial P35 employment in an outcome year are assigned a NACE code based on that of their 'main employer', which is the employer that contributes the largest earnings to the graduate within that year.
A graduate who demonstrates substantial self-employment is assigned a NACE code based on their IT Form 11 data. In cases where an individual demonstrated both substantial P35 employment and substantial self-employment within the same calendar year, and where the NACE codes from those two occupations differed, the NACE code for outcomes analysis was taken from the occupation which had the longest duration.
Note that in the case of substantial P35 employment, NACE codes describe the main activity of the employer. The activity of the graduate themselves may differ. For example, an individual carrying out research at a university would be classified as 'Education' (P), and somebody working in company law for a restaurant chain would be classified as 'Accommodation and Food Service Activities' (I). No occupation code which describes the type of work carried out is currently available in the administrative data. The results may therefore differ with other forms of research but are useful nonetheless for comparison across parameters such as sex and field of study.