Survey of Financial Security (SFS)

Detailed information for 2012

The purpose of the survey is to collect information from a sample of Canadian households on their assets, debts, employment, income and education. The SFS provides a comprehensive picture of the net worth (or financial health) of Canadians. Information is collected on the value of all major financial and non-financial assets and on the money owing on mortgages, vehicles, credit cards, student loans and other debts.

Data release - February 25, 2014

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

Description

The SFS provides a comprehensive picture of the net worth of Canadians. Information is collected on the value of all major financial and non-financial assets and on the money owing on mortgages, vehicles, credit cards, student loans and other debts. A family's net worth can be thought of as the amount of money they would be left with if they sold all of their assets and paid off all of their debts.

The survey data are used by government departments to help formulate policy, the private sector and by individuals and families to compare their wealth with those of similar types of families.

Reference period: The reference period is the calendar year during which collection occurs.

Collection period: The Collection period lasts 3 months, from beginning of September to beginning of December.

Subjects

• Household assets, debts and wealth
• Income, pensions, spending and wealth

Data sources and methodology

Target population

The target population for the SFS is families across the ten provinces of Canada.
Excluded from the survey are:
- the territories,
- those living on reserves and other Indigenous settlements,
- official representatives of foreign countries living in Canada and their families,
- members of religious and other communal colonies,
- members of the Canadian Forces living in military bases,
- people living in residences for senior citizens, and
- people living full time in institutions, for example, inmates of penal institutions and chronic care patients living in hospitals and nursing homes.
These exclusions represent approximately 2% of the population.

Instrument design

Qualitative testing was carried out by Statistics Canada's Questionnaire Design Resource Centre (QDRC) for selected modules of the survey questionnaire, while questions for the remaining modules came from other Statistics Canada surveys. Question wording adheres as closely as possible to questions established by the Harmonized Content Committee at Statistics Canada.

The questionnaire follows standard practices and wording used in a computer-assisted interviewing environment, such as the automatic control of flows that depend upon answers to earlier questions and the use of edits to check for logical inconsistencies and capture errors. The computer application for data collection was tested extensively.

Sampling

This is a sample survey with a cross-sectional design.

The 2012 SFS has a stratified multi-stage dual frame design. The overall initial sample size was 20,000 dwellings. The sample was selected as two independent samples from two overlapping frames: the Labour Force Survey (LFS) area frame and a frame constructed from the urban portion, that is Census Metropolitan Areas (CMAs) and Census Agglomerations (CAs), of the T1 family file (T1FF).

All families residing in the selected dwellings were included in the sample.

Data sources

Data collection for this reference period: 2012-09-04 to 2012-11-30

Responding to this survey is voluntary.

Data are collected directly from survey respondents, extracted from administrative files and derived from other Statistics Canada surveys and/or other sources.

Collection method: CAPI (computer-assisted personal interviewing)
Capture method: Blaise
Initial contact: Introductory letter sent to the respondents.
Follow up: Interviewer visits/calls respondents
proxy reporting: yes
Languages offered: English and French
Average time of interview: 45 minutes
Administration data source: Income tax Records file (T1).
Other source: Pension Plans in Canada (PPIC)
To reduce response burden, information from personal tax data and the Pension Plans in Canada survey are used.

View the Questionnaire(s) and reporting guide(s) .

Error detection

To be provided when data are released.

Imputation

For income data, all respondents are matched to the tax data file unless they refuse to have their information linked. Data obtained from the tax file are complete and do not require imputation. Only in the absence of tax data are income figures imputed. Donor imputation by the nearest neighbour method is generally used and is performed primarily with Statistics Canada's Census Edit and Imputation System (CANCEIS). However, amounts received through certain government programs such as the universal child care benefit and child tax benefits are derived from other information (i.e. number of children in the household) using a deductive imputation method.

Imputation is also performed for other key variables when information is missing. The imputation of the non-income variables was also done primarily using the nearest neighbour imputation method. In some cases deductive imputation was also used. The imputation is performed in several steps. Variables in the same sections of the questionnaire or in related sections of the questionnaire are often imputed together. An appropriate set of matching variables and imputation classes are determined for each group of variables processed together. Statistic Canada's CANCEIS and BANFF (generalized edit and imputation system) software, as well as custom SAS programs were used to perform the imputation of the non-income variables.

Imputation is also used to handle item nonresponse for many, but not all, variables. Variables not subject to imputation retain missing values in the form of "Don't Know", "Refused" and "Not Stated" reserve codes. Imputation rates for questions which applied to the majority of respondents tended to be quite low, but items that applied only to a small percentage of respondents sometimes had fairly high imputation rates indicating that the respondents were having much more difficulty answering or were less willing to provide answers to these questions.

Estimation

An integrated weight, meaning that all household members are given the same weight, is produced for SFS. The weighting process begins by calculating design weights separately for the two samples. The weights are then adjusted for non-response separately within each sample. In order to combine the two samples, the weights must be adjusted to take into account the fact that the dwellings in the overlap of the two frames have a chance of being selected in both samples. The weights are then calibrated to known population totals. The totals include demographic projections produced by Statistics Canada's Demography Division based on the 2006 Census, as well as the number of wage and salary earners by 7 wage classes by province based on the Canada Revenue Agency's T4 file. The demographic totals for each province include age/sex counts as well as household size and family size counts. Influential observations are then identified and weights are reduced for a small number of extreme observations. The weights of the remaining observations are then adjusted with another round of calibration.

Quality evaluation

Data are compared to the results of other data sources: Census, administrative and other Statistics Canada surveys.

Direct comparisons with outside sources, such as the Financial and Wealth Accounts of the System of National Accounts, are difficult to make due to definitional, coverage and treatment differences. However, based on rough comparisons the following general conclusions can be drawn:

(a) SFS appears to underestimate some net worth components, particularly financial assets and consumer debt.

(b) The quality of estimates of real assets (e.g., owner-occupied homes, vehicles) is much better than that of financial assets.

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.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

This methodology does not apply to this survey.

Data accuracy

To be provided when data are released.