Survey of Approaches to Educational Planning (SAEP)
Detailed information for 2020
Statistics Canada is conducting the Survey of Approaches to Educational Planning (SAEP) to gather information from parents and guardians about 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.
Data release - September 24, 2020
Statistics Canada was approached by Employment and Social Development Canada (ESDC) to conduct a cross-sectional survey which would examine how Canadians are preparing their children for postsecondary education.
Parents and guardians can prepare in several ways. They can proactively plan for the financing of their children's postsecondary education by putting aside savings for that purpose and by actively participating in government-sponsored mechanisms that facilitate savings for postsecondary education (e.g., Registered Education Savings Plans). They can also prepare in a non-monetary fashion by encouraging, guiding and supporting their children through their early education, thereby laying the groundwork for participation in postsecondary education.
The primary objective of the Survey of Approaches to Educational Planning (SAEP) is to gather information about the ways in which the parents and guardians of children aged 0 to 17 marshal the monetary and non-monetary resources needed to pursue postsecondary education, including financial saving strategies, families' attitudes and values with respect to postsecondary education, and barriers to saving or planning for education after high school.
The information gathered from the SAEP will be used to inform research, policies and programs that help families plan and save for their children's education after high school, and to determine Canadians' awareness of government programs that help families save for their children's postsecondary education.
- Education finance
- Education, training and learning
Data sources and methodology
The target population consists of children between the ages of 0 and 17 as of February 1, 2020 in the ten provinces. The survey was completed by a parent or guardian living in the child's household.
The SAEP questionnaire contains many of the same questions that were used in the 2013 iteration of the survey. Revisions were implemented in collaboration with Employment and Social Development Canada (ESDC), as well as internal Statistics Canada development partners such as the Questionnaire Design Resource Centre (QDRC) who conducted qualitative tests of the questionnaire and recommended changes which were incorporated when possible.
This is a sample survey with a cross-sectional design.
The survey frame is households in rotation groups that completed their six months in the Labour Force Survey (LFS) between August 2019 and January 2020, therefore its sample design is closely tied to that of the LFS.
The LFS is a monthly household survey whose sample of individuals is representative of the civilian, non-institutionalized population 15 years of age or older across Canada. Excluded from the survey's coverage are persons living on reserves and other Indigenous settlements in the provinces, full-time members of the Canadian Armed Forces, the institutionalized population, and households in extremely remote areas with very low population density. These groups together represent an exclusion of less than 2% of the population aged 15 or over.
Residents of the Yukon, Northwest Territories, and Nunavut are included in the LFS but collection is done at different intervals. They are excluded from the SAEP sample frame.
The LFS follows a rotating panel sample design, in which households remain in the sample for six consecutive months. The total sample consists of six representative sub-samples or panels, and each month a panel is replaced after completing its six month stay in the survey.
The SAEP sample is based on the rotate out group from each LFS collection from August 2019 to January 2020. For the SAEP, the coverage of the LFS was modified to include only those households with at least one child aged 17 and under. Within those households, one child was randomly selected.
Data collection for this reference period: 2020-02-04 to 2020-06-20
Responding to this survey is voluntary.
Data are collected directly from survey respondents and derived from other Statistics Canada surveys.
The SAEP is collected by way of self-response electronic questionnaire with telephone interview follow-up. Information is collected from the person who is most knowledgeable about the selected child and any plans for their postsecondary education. Proxy response was not allowed.
View the Questionnaire(s) and reporting guide(s) .
The electronic questionnaire (EQ) included automated logical flows to control the questions that were asked to respondents and a limited number of soft edits that checked for unusual values or inconsistencies.
The collected data was processed at head office, including:
- the coding of write-in responses to existing response categories (new response categories were created as needed);
- the use of consistency edits to check for logical inconsistencies or extreme values, and;
- the creation of derived variables to aid with analysis.
Total non-response was handled by adjusting the weight of households who responded to the survey to compensate for those who did not respond.
In most cases, partial non-response to the survey occurred when the respondent did not understand or misinterpreted a question, refused to answer a question, or could not recall the requested information.
For the 2020 SAEP, donor imputation was used to fill missing data in household income, type(s) of savings methods used, and Registered Education Savings Plan (RESP) value. This was done in order to provide complete data, thereby allowing for totals to be estimated (e.g., total group RESP contributions in Ontario).
The methods of savings were imputed for cases that have or had savings set aside for their child's postsecondary education but did not report any methods of savings. If RESPs were one of the methods imputed, then the value of the RESPs is also imputed using the same donor. Then the RESP value was imputed for the cases that mentioned using RESPs, did not report any amount and did not mention that the RESPs started in 2020.
Imputation involved filling the missing values in household income, savings method, and RESP value on a given record (the "recipient" record) using another record whose values were all known and whose characteristics were the "closest" (the "donor" record). The characteristics of each recipient were compared to those of each donor in a pool of donors. When a characteristic between the recipient and a donor were the same, the weight (value) of that characteristic was added to a "score" for that donor. In the end, the donor with the highest score was deemed to be the closest, and was therefore chosen to fill the missing value(s) in the recipient. If there was more than one donor with the highest score, one donor was randomly selected. The pool of donors was made up in such a way that the imputed value assigned to the recipient, in conjunction with other non-imputed items from the recipient, would still pass the edits.
Donor imputation was done in three steps. First, household income was imputed. This is partly because household income is an important factor in the donor score when imputing key items. Second, the savings methods and RESP value (if RESPs were imputed as a savings method used) were imputed. These variables were imputed simultaneously for consistency and coherence. Then RESP value was imputed for the cases who reported using an RESP.
The principle behind estimation in a probability sample such as the LFS is that each person in the sample "represents", besides himself or herself, several other persons not in the sample. For example, in a simple random 2% sample of a population of 2,500 persons, each person in the sample represents 50 persons in the population.
The weighting phase is a step which calculates, for each record, what this number is. This weight appears on the microdata file, and must be used to derive meaningful estimates from the survey. For example, if the number of children whose parents/guardians have set aside savings for postsecondary education is to be estimated, it is done by selecting the records referring to those individuals in the sample with that characteristic and summing the weights entered on those records.
The principles behind the calculation of the weights for the SAEP are identical to those for the LFS. However, 5 adjustments are made to the LFS sub-weights in order to derive a final weight for the individual records on the SAEP microdata file:
1) An adjustment to account for the number of LFS months used. For this version of SAEP, 6 months were used, which correspondents to a full LFS sample. Thus there is no adjustment for this cycle.
2) An adjustment to account for the additional non-response to the supplementary survey i.e., non-response to the SAEP for households with at least one child aged 0 to 17 years which did respond to the LFS or for which the previous month's LFS data was brought forward. The procedure is similar to the LFS non-response weight adjustment, but the groupings are based on province, rotation group, design type, urban area versus rural area, census metropolitan area versus non-census metropolitan area, type of dwelling, economic family type, household size, and parent/guardian characteristics such as education, labour force status and occupation. Since households without children are out-of-scope (and therefore not selected into the SAEP), their weights are not affected by this step.
3) An adjustment for the total number of households (i.e., those with or without at least one child aged 0 to 17 years) by household size (1, 2 and 3+ people) and by province, according to independent estimates.
4) An adjustment to account for the random selection of one child from the selected household. In particular, the weight of the selected child is multiplied by the number of children in the household, up to a maximum (cap) of four children.
5) An adjustment for the number of children by province, sex, and age group (i.e., 0 to 5, 6 to 12, 13 to 15 and 16 to 18 years), according to independent estimates.
The resulting weight, WTPM, is the final weight which appears on the SAEP master file.
Data were confronted with other published sources such as the 2013 Survey of Approaches to Educational Planning.
For the data tables, the data were released under the coefficient of variation release guidelines. The quality level of an estimate will be determined only on the basis of sampling error as reflected by the coefficient of variation.
Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.
Revisions and seasonal adjustment
This methodology does not apply to this survey.
The response rate for SAEP 2020 was 59.8%.
Sampling error occurs because population estimates are calculated from a sample of the population rather than the entire population. Sampling error depends on factors such as sample size, sampling design, and the method of estimation.
The basis for measuring the potential size of sampling errors is the standard error of the estimates calculated from survey data. Because of the large variety of estimates that can be produced from a survey, the standard error of an estimate is usually expressed relative to the estimate to which it pertains. This resulting measure, known as the coefficient of variation (CV) of an estimate, is obtained by dividing the standard error of the estimate by the estimate itself and is expressed as a percentage of the estimate.
Users should determine the coefficient of variation of the estimate in order to get an indication of the quality of the estimates. For instance, if the coefficient of variation is less than 16%, the estimates can be used without any restriction; if it is between 16% and 33%, the estimates should be used with caution; and, if it is 33% or more, the estimates cannot be released in any form under any release.
In addition, non-sampling errors may occur at almost every phase of the survey operation. Considerable time and effort was made to reduce non-sampling errors in the survey. Quality assurance measures were implemented at each step of the data collection and processing cycle to monitor the quality of the data.