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Survey of Financial Security (SFS)
This survey provides information of the net worth (wealth) of Canadian families, that is, the value of their assets less their debts.
Detailed information for 2012
Data release – planned for December 2013
Description
The purpose of the survey is to collect information from a sample of Canadian households on their assets, debts, employment, income and education. This helps in understanding how household finances change because of economic pressures.
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 households
Subjects
- Household assets, debts and wealth
- Household spending and savings
- Income, pensions, spending and wealth
Data sources and methodology
- Target population
- Instrument design
- Sampling
- Data sources
- Error detection
- Imputation
- Estimation
- Quality evaluation
- Disclosure control
Target population
The Survey of Financial Security is carried out in all ten provinces, the territories are not included. Those living on Indian reserves and crown lands and official representatives of foreign countries living in Canada and their families are also excluded from the survey. Members of religious and other communal colonies, members of the Canadian Forces living in military camps and people living in residences for senior citizens are excluded, as are people living full time in institutions, for example, inmates of penal institutions and chronic care patients living in hospitals and nursing homes. The survey covers about 98% of the population in the ten provinces.
Instrument design
The questionnaire content is determined in consultation with Human Resources and Social Development Canada, the Bank of Canada, Canada Mortgage and Housing Corporation, Finance Canada and Industry Canada.
Sampling
This is a sample survey with a cross-sectional design.
The sample for the 2012 Survey of Financial Security is drawn from two sources (Labour Force Survey area frame and T1 Family File frame) and consists of approximately 20,000 dwellings. The sample is divided between urban (Census metropolitan areas (CMA) and Census agglomerations (CA)) and rural areas. About 12,300 dwellings are selected in urban areas - approximately 8,300 of them are drawn from the T1 Family File frame and the remaining 4,000 from the Labour Force Survey area frame. The entire rural area sample of approximately 7,700 dwellings is drawn from the Labour Force Survey area frame. All families living in each selected dwelling are interviewed.
Data sources
Data collection for this reference period: 2012-09-04 – 2012-11-30
Responding to this survey is voluntary.
Data are collected directly from survey respondents and extracted from administrative files.
Interviews are conducted using a Computer-Assisted Personal Interviewing (CAPI) application. Respondents are encouraged to use bills and other material to provide a more accurate response. The average interview last approximately 45 minutes.
Information is not gathered from persons temporarily living away from their families (for example, students at university), because it would be gathered from their families if selected. In this way, double counting of such individuals are avoided.
The interview is held with the family member with most knowledge of the family's financial situation. If necessary, follow-up is done with other family members. Proxy response is accepted. This allows one family member to answer questions on behalf of any or all other members of the family, providing he or she is willing and able to do so.
Use of administrative data:
To reduce response burden, information from personal tax data and Pension Plans in Canada survey is used.
View the Questionnaire(s) and reporting guide(s)
Error detection
Treatment of Large Values
For any sample, estimates can be affected disproportionately by the presence or absence of extreme values from the population. In an asset and debt survey, a few extreme values are expected in the sample, as valid extreme values do exist in the population. Values outside defined bounds are identified and reviewed in relation to other information reported for that respondent. If the value is judged to be the result of a reporting or processing error, it is adjusted. Otherwise, it is retained.
Imputation
Missing responses are imputed for all key fields in the questionnaire. Where possible, information are imputed deterministically, using other information reported by the respondent. For example, if the respondent cannot estimate the value of their vehicle, the reported make, model and year is used to impute a value. This value can be determined by consulting a reference book. When deterministic imputation is not possible, hotdeck imputation methods are used in most cases, and for all components of income and net worth, nearest neighbour techniques are employed. These methods involve identifying another individual or family with similar characteristics to become the "donor" and provide the imputed value. Income data obtained from tax returns are considered complete and thus do not require imputation.
Estimation
Weighting
The population totals used for the SFS are based on Statistics Canada's Demography Division population counts for different province - age - sex groups. The weights are also adjusted to ensure that the number of 1-person, 2-person, and 3 or more-person households and family units agreed with known totals by province. Additionally, a weight adjustment based on administrative data from the T4 file is performed. This weight adjustment is made to ensure that the survey distribution of earnings reflects approximately the same distribution as the T4 population.
Quality evaluation
Data are compared to the results of other data sources: Census, administrative and other Statistics Canada surveys.
Disclosure control
Statistics Canada is prohibited by law from releasing any information it collects which 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.
Data accuracy
1. Impact of sampling and non-sampling errors on SFS estimates
Due to the combined effect of these errors, the quality of net worth data is judged to be lower than the quality of income data. This is largely because records of the current value of assets and the outstanding amount of debt are not as readily available as records of income. For example, respondents with numerous bank accounts and investments may receive several different statements, with different reference periods. Compiling this information can be difficult; most income information, on the other hand, would be available in one document, if the respondent had completed an income tax return for the year in question.
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.
2. Coefficients of variation
Data reliability of the survey estimates are assessed based on the calculated coefficients of variation. Estimates with a coefficient of variation less than 33% are considered reliable for general use. Estimates with coefficients of variation greater than 33% are deemed to be unreliable.
