Technical Reference Guides for the Education and Labour Market Longitudinal Platform (ELMLP)
Overview of the Education and Labour Market Longitudinal Platform and Associated Datasets, 2022

Release date: June 6, 2022

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1. Introduction

Statistics Canada, in collaboration with the provincial and territorial ministries of education, Employment and Social Development Canada (ESDC), and other stakeholders, has developed the Education and Labour Market Longitudinal Platform (ELMLP).

The ELMLP allows longitudinal integration of administrative data related to education with other data sources to create anonymized, customized datasets for analytical purposes.

The ELMLP fills data gaps and enables a greater understanding of student and apprenticeship pathways, transitions to the labour market and outcomes over time. Data from the ELMLP can help address a wide range of policy questions pertaining to student and apprenticeship persistence, completion, mobility and pathways as well as their labour market outcomes.

These data allow policy makers to understand the different types of trajectories that students can take through their postsecondary education or apprenticeship training as well as student characteristics that may be related to these trajectories.

The target users for the ELMLP include provincial and territorial ministries of education, apprenticeship authorities, postsecondary educational institutions, federal government departments, members of the academic community, researchers, students and parents interested in graduate outcomes and other stakeholder groups involved in education and the labour market.

2. The Education and Labour Market Longitudinal Platform (ELMLP)

2.1 The key features of the ELMLP

  1. Platform – The ELMLP allows researchers to integrate selected datasets to access information about past cohorts of college/university students and registered apprentices, in order to better understand their pathways and the ways in which education and training affected their career prospects.
  2. Securely integrable datasets – These datasets that can be integrated allow researchers to know more than what a single dataset or survey can provide. Securely integrable datasets means that any of the datasets in the ELMLP may be combined with any other dataset using an anonymous linkage identifier found on each file. The integration of datasets is carried out within the Statistics Canada Social Data Linkage Environment (SDLE), which maintains the highest privacy and data security standards. The ELMLP is not a large integrated dataset, but rather a relational data environment. Researchers are only given access to the files necessary for their analysis. After identifying which ELMLP datasets are needed to answer a specific research or policy question, researchers can use the anonymous identifier located on each file to bring these datasets together.
  3. Longitudinal data – The data available within the Platform can be linked longitudinally, allowing researchers to better understand the characteristics, pathways and outcomes of students and apprentices over time.
  4. Accessible data – Datasets prepared for the Platform are made available to researchers through the Research Data Centre (RDC) network across Canada.

2.2 Accessibility, confidentiality and privacy

Datasets that are integrated in the ELMLP are deemed sensitive statistical information and are subject to the confidentiality requirements of the Statistics Act. Statistics Canada employees who work with the integrated datasets for research purposes have access to the data only after they have been stripped of personal identifiers. Furthermore, only Statistics Canada employees and deemed employees who have an approved need to access the data for their analytical work are allowed access to the files.

These data are treated with the same level of confidentiality as surveys administered by Statistics Canada.

Indicators, analysis and findings from the ELMLP are released through Statistics Canada’s website.

The anonymized ELMLP data are also available in Statistics Canada’s Research Data Centres (RDC) to researchers with approved projects only. These researchers are provided with access in a secure setting at the RDCs, which are staffed by Statistics Canada employees. The RDCs operate under the provisions of the Statistics Act in accordance with all confidentiality rules, and are only accessible to researchers once they have been sworn in under the Statistics Act as “deemed employees.” All analytical results are vetted before they can be taken out of the RDCs to ensure that confidentiality is maintained and individuals cannot be identified.

2.3 Core and supplementary datasets

The ELMLP consists of two types of datasets: core and supplementary.

Core datasets are updated in the ELMLP on an annual basis to include the most recently released data.  

SupplementaryNote 1 datasets are updated with a frequency that varies according to a number of factors and may not always include the most recent data years.

Core datasets
The core datasets are:

  1. The Postsecondary Student Information System (PSIS) – an annual administrative dataset of all Canadian (provincial and territorial) public college and university enrolments and graduations by type of program, type of credential, and field of study for each reporting year. PSIS collects information pertaining to the programs and courses offered at an institution, as well as demographic information for the students and the program(s) and course(s) in which they were registered, or from which they have graduated. PSIS is also designed to collect continuing education data. The ELMLP includes PSIS data from academic year 2009/2010 onwards for all provinces and territories. For more information, see Statistics Canada’s PSIS information page.
  2. The Registered Apprenticeship Information System (RAIS) – an annual administrative dataset of all Canadian (provincial and territorial) registered apprentices and trade qualifiers. The RAIS compiles data on the number of registered apprentices taking in-class and/or on-the-job training in trades that are either Red Seal or non-Red Seal and where apprenticeship training is either compulsory or voluntary. It also compiles data on the number of provincial and interprovincial certificates granted to apprentices or trade qualifiers (challengers). The purpose of the RAIS is to gather information on individuals who receive training and those who obtain certification within a trade where apprenticeship training is being offered. The ELMLP includes RAIS data from 2008 onward. For more information, see Statistics Canada’s RAIS information page.
  3. Income tax from the T1 Family File (T1FF), subset for the PSIS and RAIS populations – an annual administrative dataset which includes selected information from income tax data from 1992 onwards for the PSIS and RAIS populations, when available. The source T1 Family File (T1FF) covers Canadian tax-filers and their families and is derived from T1 income tax returns. For the most part, tax returns were filed in the spring of the year following the reference year. Income information is based on the calendar year. There is no T1FF datafile available in the ELMLP that includes the total tax-filing population of CanadaNote 2 . For more information, see Statistics Canada’s T1FF information page.

Supplementary datasets

The supplementary files are:

  1. 2016 Census of Population, Long Form – a dataset that provides information about the Canadian population, including characteristics such as age, sex, type of dwelling, families, households and marital status, and language. For the 2016 Census, Canadian households were enumerated using two main types of questionnaires: the short-form questionnaire and the long-form questionnaire. The long-form questionnaire includes the same questions as the short form, as well as a series of questions, such as those about visible minorities, aimed at providing a more comprehensive portrait of the Canadian population and Canadian households. The long-form questionnaire was sent to a sample of the population covering approximately 1 in 4 households. For more information, see Statistics Canada’s Census information page.
  2. Longitudinal Administrative Databank (LAD), 1982 to 2019 – an administrative longitudinal dataset designed as a research tool on income and demographics. It uses a longitudinal sample of 20% of the records in the annual T1 Family File representing the total population Canadian tax-filers and their families. It can be used as a control group or for residual group analysis. For more information, see Statistics Canada’s LAD information page.
  3. Longitudinal Immigration Database (IMDB), 1952 to 2020 an administrative longitudinal dataset that includes immigration data for all immigrants since 1952 and non-permanent residents since 1980. Outcomes for this population are available from tax files since 1982. The IMDB provides detailed information on socioeconomic outcomes of immigrants after their admission. For more information, see Statistics Canada’s IMDB information page.
  4. 2018 National Graduates Survey (NGS), Class of 2015 – a dataset containing information from a sample survey of graduates of public postsecondary educational institutions in Canada for the class of 2015. The questions focus on academic path, funding for postsecondary education (including government-sponsored student loans), and transition into the labour market. New cycles of this survey take place every 5 years. For more information, see Statistics Canada’s NGS information page.
  5. BC Kindergarten to grade 12 data (BC K-12), 1991/1992 to 2020/2021 an administrative dataset which provides student-level information for students who attended British Columbia’s public and independent schools during the reference period. The data includes information about student characteristics (gender, age, geographic location, etc.) and progress through the education system (graduation, Foundation Skills Assessment results, exam marks, etc.).
  6. Canada Student Loans Program (CSLP) (now Canada Student Financial Assistance Program (CSFA)), 2003/2004 to 2015/2016 an administrative dataset which provides information on both non-repayable and repayable student financial assistance (grants and loans) to eligible students to help them access and afford postsecondary education. The CSLP data provides information on needs assessment, disbursement and repayment of loans and grants. All provinces and territories participate in the CSLP, except Quebec, the Northwest Territories and Nunavut, who receive alternative payments from the Government of Canada to administer their own student financial aid programs. The CSLP data at Statistics Canada only reflects the federal portion of student financial aid (i.e. not any provincial or territorial student financial aid). Federal-provincial/territorial arrangements vary by jurisdiction.
  7. Canada Education Savings Program (CESP), 1998 to 2020 – administrative datasets which include information on the CESP and the Canada Learning Bond (CLB) program, both of which are federal savings incentive programs that are available for eligible Registered Education Savings Plan (RESP) beneficiaries. It includes information on the RESP, an Education Savings Plan that has been registered with the Canada Revenue Agency. It is a savings vehicle used by individuals and families to save for children's postsecondary education. The CESP and the CLB programs provide additional government grants for postsecondary studies based on the original RESP contributions and other criteria. The files provide information on the beneficiaries, the subscribers and the primary caregivers and on contributions, grants and withdrawals.
  8. Canada Apprentice Loans (CAL), 2015 to 2021 an administrative data file which provides information on those who are eligible to receive loans during the period in which they are registered in Red Seal apprenticeships and are taking technical training. The loans help cover the costs of apprenticeship training.
  9. Apprenticeship Incentive Grants (AIG), 2007 to 2021 – an administrative data file which provides information on taxable cash grants for those registered with their provincial/territorial apprenticeship authority as an apprentice. To receive it, applicants are required to prove that they have successfully completed either the first and/or second year or level (or equivalent) in a designated Red Seal tradeNote 3 .
  10. Apprenticeship Completion Grant (ACG), 2009 to 2021 – an administrative data file that provides information about one-time taxable cash grants designed to encourage apprentices to complete their apprenticeship programNote 3.
  11. Apprenticeship Incentive Grant for Women (AIG-W), April 1st 2018 to 2021 – an administrative data file which provides information on taxable cash grants for women registered with their provincial/territorial apprenticeship authority as an apprentice. To receive it, applicants are required to prove that they have successfully completed either the first and/or second year or level (or equivalent) in a designated Red Seal trade where women are underrepresentedNote 3 .
  12. National Apprenticeship Survey (NAS), 2015 – a dataset containing information from a sample survey that looks at factors affecting the completion, certification and transition of apprentices to the labour market. For more information, see Statistics Canada’s NAS information page.
  13. Employment Insurance Status Vector (EISV), 2007 to 2018 – an administrative dataset that follows the trajectory of Employment Insurance (EI) claims and benefit payments from application to termination. It describes the characteristics of the EI claimants, provides summary information for the claim and a week by week account of claimant activity during the life of the claim.
  14. Survey of Approaches to Educational Planning (SAEP), 2020 – a dataset containing information from a sample survey that gathers information from parents and guardians of children aged 0 to 17 about their attitudes and expectations with respect to their child’s postsecondary education, the strategies they use to prepare for their children's postsecondary education, their financial plans for paying for their schooling, and the barriers to saving for higher education. The dataset also includes demographic and labour force status information. For more information, see Statistics Canada’s SAEP information page.
  15. Emergency and recovery benefits (ERB), March to September 2020 – this dataset is intended to cover the major income support measures offered to Canadians as a result of the COVID-19 pandemic in 2020 and 2021. These direct support programs include the Canada Emergency Response Benefit (CERB), the Canada Emergency Student Benefit (CESB), the Canada Recovery Benefit (CRB), the Canada Recovery Caregiving Benefit (CRCB) and the Canada Recovery Sickness Benefit (CRSB). Currently, only the CERB (March to September 2020) portion is available in the RDCs. For more information, see Statistics Canada’s ERB information page.
  16. T1FF for PSIS and RAIS — parental income variant (Consumer Price Index-adjusted), 1992 to 2019 – an administrative dataset derived from the T1 Family File (T1FF) subset file, for the Postsecondary Student Information System (PSIS) and the Registered Apprenticeship Information System (RAIS), that provides information on the income of parents of postsecondary students, registered apprentices and trade qualifiers. The dataset is available for analytical convenience, as all of the variables can be re-derived using the T1 Family File of the ELMLP core files.

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