Survey of Approaches to Educational Planning (SAEP)

Detailed information for 2025

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 schooling, and the barriers to saving for higher education.

Data release - February 20, 2026

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

Statistics Canada was approached by Employment and Social Development Canada (ESDC) to conduct a cross-sectional survey to 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 by encouraging, guiding and supporting their children through their early education, thereby laying the groundwork for pursuing 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 6 months to 17 years marshal the monetary and non-monetary resources needed to pursue postsecondary education. This includes financial saving strategies, familial 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.

Subjects

• Education finance
• Education, training and learning

Data sources and methodology

Target population

The target population consists of children between the ages of 6 months and 17 years as of May 16th, 2025 living in the ten provinces. Children living on reserves are excluded from the target population.

Instrument design

The SAEP questionnaire contains many of the same questions that were used in the 2020 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.

Sampling

This is a sample survey.

Survey frame:
The SAEP sample was selected from the Canada Child Benefit (CCB) file.

Sampling unit:
This is a targeted respondent survey. The sampling unit is the person knowledgeable (aged 15 years or older) about the postsecondary education plans for a child who lives in their household and is aged 6 months to 17 years as of May 16, 2025.

Stratification method:
No stratification for SAEP. It is a simple random sample at the national level.

Sampling and sub-sampling:
Sufficient sample was allocated to each of the provinces so that the survey could produce national level estimates and allow for further data disaggregation compared to previous SAEP cycles.

An initial sample of 40,000 targeted respondents was selected and sent to collection.

The selection of a sample unit is done in one stage. The frame is sorted geographically, then a systematic random sample of eligible children is selected. A child is eligible if they are less than 18 years old as of May 16, 2025.

Data sources

Data collection for this reference period: 2025-02-24 to 2025-05-20

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) .

Error detection

Electronic files containing the daily transmissions of completed respondent survey records were combined to create the "raw" survey file. Before further processing, verification was performed to identify and eliminate potential duplicate records and to drop non-response and out-of-scope records.

In addition, some out-of-scope respondent records were found during the data clean-up stage. All respondent records that were determined to be out-of-scope and those records that contained no data were removed from the data file.

After the verification stage, editing was performed to identify errors and modify affected data at the individual variable level. The first editing step was to identify errors and determine which items from the survey output needed to be kept on the survey master file. Subsequent to this, invalid characters were deleted, and the remaining data items were formatted appropriately.

Imputation

Imputation is a process used to determine and assign replacement values to resolve problems of missing, invalid or inconsistent data. This is done by changing some of the missing values and the responses on the record being edited to ensure that a plausible, internally consistent record is created.

For the 2025 SAEP, total household income was imputed using donor imputation for cases with missing values. The missing income values on a given record (the "recipient" record) are filled using another record whose value is known (the "donor" record). The donor is chosen randomly from a pool of donors who share similar characteristics to the recipient, based on survey responses and other administrative data.

Province were not asked on the questionnaire. These missing values were imputed with using the values from the sample file.

Estimation

The estimation of population characteristics from a sample survey is based on the premise that each person in the sample represents a certain number of other persons in addition to themselves. This number is called the 'survey weight'. The process of computing survey weights for each survey respondent involves several steps. This weight appears on the microdata file and must be used to derive meaningful estimates from the survey.

1) Each selected respondent is given an initial weight equal to the inverse of its selection probability from the sampling frame (CCB). Respondents identified as out-of-scope during collection are dropped from the sample.

2) The respondents' weights are then adjusted to account for non-response based on geography and household characteristics.

3) 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.

4) The person (child) weights are calibrated so that the sums of weights match demographic population counts at the level of province by age by gender.

Variance estimation is based on a re-sampling method called bootstrap estimation.

The Generalized Estimation System from Statistics Canada (G-Est) was used to generate the survey weights and bootstrap weights.

Quality evaluation

While rigorous quality assurance mechanisms are applied at all stages of the statistical process, the validation and detailed review of data by statisticians is the ultimate verification of quality prior to release. Many validation measures were implemented, they include:

a. Verification of estimates through cross-tabulations
b. Consultation with stakeholders internal to Statistics Canada
c. Consultation with external stakeholders.

Disclosure control

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.

Data accuracy

Survey errors come from a variety of different sources. One dimension of survey error is sampling error. Sampling error is defined as the error that arises because an estimate is based on a sample rather than the entire population. Sampling error depends on factors such as sample size, sampling design, and the method of estimation. Sampling error can be expressed through a confidence interval (CI) or coefficient of variation (CV).

The following are approximate sampling error estimates for Canada level estimates. These are not results for any specific variable.

- Approximate length of 95% confidence intervals for a proportion of 50% (Canada level): 1.8%
- Approximate length of 95% confidence intervals for a proportion of 10% (Canada level): 1.1%
- Approximate coefficients of variation a proportion of 10% (Canada level): 2.8%

Response rates:
The response rate for SAEP 2025 is 40.9%.

Non-sampling error:
The first type of errors treated were errors in questionnaire flow. For skips based on answered questions, all skipped questions were set to "Valid skip" (6, 96, 996, etc.). For skips based on "Non-response", all skipped questions were set to "Not stated" (9, 99, 999, etc.). The remaining empty items were filled with a numeric value (9, 99, 999, etc., depending on variable length). These codes are reserved for processing purposes and mean that the item was "Not stated".

Non-response bias:
The survey estimates are adjusted to account for non-response through the survey weights. To the extent that the non-responding persons differ from the rest of the sample, the results may be biased.

Coverage error:
Coverage errors arise when there are differences between the target population and the observed population. The target respondent is the person knowledgeable (aged 15 years and older) about the child who lives in the household and is aged 6 months to 17 years. The survey frame is the Canada Child Benefit (CCB) file, and it contains every parent or guardian who is registered to receive a benefit. It is estimated that the frame represents 92% of the target population. Excluded from the target population are individuals living in a collective dwelling, an institution or on a First Nation reserve. These exclusions represent approximately 2% of children aged between 6 months and 17 years old. To the extent that the excluded population differs from the rest of the target population, the results may be biased.