Survey of Household Spending (SHS)

Survey of Household Spending (SHS)
Variable(s)
Summary of changes
Other reference periods
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Detailed information for 2023

Status:

Active

Frequency:

Every 2 years

Record number:

3508

The main purpose of the Survey of Household Spending (SHS) is to obtain detailed information about household spending, as well as limited information on dwelling characteristics and household equipment.

Data release - May 21, 2025

Description

The SHS primarily collects detailed information on household expenditures. It also collects information about the annual income of household members (from personal income tax data), demographic characteristics of the household, dwelling characteristics (e.g., type, age and tenure) and household equipment (e.g., electronics and communications equipment). The SHS is conducted in the 10 provinces and the 3 territorial capitals every two years, starting with the 2017 reference year.

SHS data are used at Statistics Canada by the Canadian System of Macroeconomic Accounts as an input to calculate gross domestic product and by the Consumer Prices Division to calculate basket weights for the Consumer Price Index. In addition, federal and provincial governments use the data to develop social and economic policies and programs. Various groups also use the data to address issues that are directly or indirectly related to Canadians' spending habits.

Collection period: The data are collected on a continuous basis from January to December of the survey reference year, from a sample of households spread over 12 monthly collection cycles.

Subjects

  • Families, households and housing
  • Household characteristics
  • Household spending and savings
  • Housing and dwelling characteristics
  • Income, pensions, spending and wealth

Data sources and methodology

Target population

The target population is resident households of Canada's 10 provinces and the capitals of the 3 territories—Whitehorse, Yellowknife and Iqaluit. People living on Indian reserves are excluded, as are institutional households, which consist of groups of people living in collective dwellings (or institutions), such as members of the Canadian Forces living in military camps. In total, these exclusions account for about 2% of the population.

People living in other types of collective dwellings may be identified during collection and are also excluded. These include, for example, members of religious and other communal colonies, people living in residences for dependent seniors, and people living permanently in school residences or work camps. These exclusions make up less than 0.5% of the target population. However, these people are included in the population estimates to which the SHS estimates are adjusted.

For operational reasons, people living in some remote areas where the rate of vacant dwellings is very high and where the collection cost would be exorbitant are excluded from collection.

Instrument design

Since 2010 in the provinces and since 2015 in the three territorial capitals, the SHS data have been collected using both a questionnaire and an expenditure diary. The questionnaire is generally used to collect expenditures for more expensive and less frequently purchased goods and services. The diary is used to collect expenditures for smaller, less valuable items and those purchased more frequently. These expenditures may be more difficult to recall.

When this new collection model was introduced, each of the expenditure items covered by the SHS was assigned to a collection mode: the questionnaire or the diary. For the questionnaire items, a recall period was also selected: 1, 3 or 12 months; last payment; or four weeks. The choice of recall period for each item was largely based on the results of qualitative tests, international best practices and studies of estimate variability when reference periods were shortened. These studies were based on data from the Consumer Expenditure Surveys conducted by the U.S. Bureau of Labor Statistics.

The content of the questionnaire and changes to it have been determined in consultation with primary internal and external users of the survey data. When changes have been made, the content has been retested using cognitive interviews and updated based on the feedback received.

In 2021, SHS collection moved from computer-assisted personal interviewing to a self-completed electronic questionnaire, following the public health measures taken for the COVID-19 pandemic. The diary was sent to respondents by mail. The collection strategy for the 2023 SHS was the same as that for the 2021 SHS, except for Iqaluit, where in-person interviews were conducted for the whole sample.

Sampling

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

Sampling unit
For the 2023 SHS, in the 10 provinces, the final sample was obtained from two distinct sampling designs. The first sampling design has two stages: the sampling unit in the first stage is the geographical area (called a cluster), and in the second stage it is the dwelling. For the second sampling design, the sampling unit is the dwelling.

In the three territorial capitals, the sampling unit is the dwelling.

Stratification method
A stratified multi-stage sampling design is used to select the first sample in the 10 provinces. It is essentially a two-stage design, and the first stage is to select a sample of geographic areas (the clusters). Next, a list of all the dwellings in the selected clusters is prepared, and a sample of dwellings is selected within each cluster. The selected dwellings that are inhabited by members of the target population constitute the survey's sample of households. The SHS uses several components of the sample design for the Labour Force Survey (LFS) to minimize operating costs, though the dwellings selected for the SHS are different than those selected for the LFS.

A stratified one-stage sampling design is used to select a second sample, which is combined with the first sample before collection. Selected dwellings that are inhabited by members of the target population are included in this second sample of households. This second sample is stratified in the same way as the first sample.

The national sample is first allocated among the provinces based on the variability of total household expenditures and, to a lesser extent, the number of households in each province. The goal is to obtain estimates of similar quality across all provinces. The sample is then divided into strata defined by grouping clusters with similar characteristics based on several sociodemographic variables. Some strata are defined to target specific subpopulations, such as high-income households. To improve the quality of the estimates, the high-income household strata are allocated a larger share of the sample than the allocation proportional to stratum size that is used in other strata.

A one-stage sampling design is used to select the sample in the three territorial capitals. The first step of the sample allocation is to determine the number of dwellings to be sampled in each city. The overall sample is allocated to each city, accounting for the size of the city and the quality of the estimates obtained from previous cycles of the SHS in the north.

Sampling and subsampling
The sample for the 2023 SHS consists of 36,320 households across the 10 provinces and 2,321 households in the 3 territorial capitals.

Because data are collected monthly, the sample is divided into 12 subsamples of similar size.

Data sources

Data collection for this reference period: 2023-01-01 to 2023-12-31

Responding to this survey is voluntary.

Data are collected directly from survey respondents and extracted from administrative files.

For the 2023 SHS, all sampled households received a letter inviting them to complete the electronic questionnaire online (except for Iqaluit, where respondents were contacted by an interviewer). All households also received a paper spending diary to complete during a specified reference period. Non-response follow-up for both the main electronic questionnaire and the diary is done at different stages of the collection period.

The electronic questionnaire mainly collects regular expenditures (such as rent and electricity) and less frequent expenditures (such as furniture and dwelling repairs) for a recall period that varies in length, depending on the type of expenditure. For regular expenditures, the amount of the last payment and the period it covers are typically collected. For other types of expenditures collected in the questionnaire, recall periods include two weeks, as well as 3 or 12 months. The recall periods are defined in terms of weeks or months preceding the month of the interview. For example, for a household in the June sample, "the last three months" corresponds to the period from March 1 to May 31. For questions that use a two-week recall period, the period corresponds to the two weeks immediately preceding collection. Demographic characteristics, dwelling characteristics and household equipment information, which are also collected in the questionnaire, refer to the household's situation at the time of collection.

For the expenditure diary, respondents are asked to record the expenditures of all household members for a specified period. Respondents in the provinces are asked to complete the diary for a one-week period, and those in the territorial capitals are asked to complete it for a two-week period. Households are required to include all of their spending, except for a few types of expenditures, such as rent and regular utility payments, as well as real estate and vehicle purchases. Households have the option of providing receipts for purchases made during the diary reporting period to reduce the amount of information they need to record manually in the diary. However, they are asked to write additional information on the receipt if the description of the item on the receipt is incomplete.

A telephone follow-up is carried out a few days after the questionnaire is completed to address any questions the respondent may have about the diary and to provide important information about how it should be completed and returned.

The diaries and all receipts supplied by respondents are scanned and captured at Statistics Canada's head office. An expenditure classification code is assigned to each item from a list of over 650 different codes.

Household income for the SHS is derived by linking income tax information from the Canada Revenue Agency to household members. Respondents are informed that the survey data will be combined with tax data to obtain personal income information for household members aged 16 and over on December 31 of the calendar year preceding the survey year. Income is imputed for individuals who do not agree to have their tax data linked, as well as for those with an unsuccessful linkage to income tax information.

The SHS links income tax data to survey respondents using deterministic and probabilistic record linkage techniques.

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

Error detection

The electronic questionnaire includes many features designed to maximize the quality of the data collected. For example, some edits are built into the questionnaire. These apply checks to detect missing, invalid or inconsistent entries by comparing the reported data with tolerance thresholds. When an edit is triggered, the respondent is prompted to correct the information. Once the data are transmitted to Statistics Canada's head office, a series of verification steps is completed to correct invalid responses or flag them for imputation.

Several edits are also carried out on the diary data when the diaries are received at the head office and throughout the capture and coding stages of data processing. For example, checks are carried out to ensure that the start and end dates of the reference period of the diary are indicated, that the reported expenditures were made during the specified reference period, and that there are no duplicated items that appear both in the diary and in the receipts provided by the respondent. When these validation, capture and coding steps are complete, a sample of diaries is completely rechecked to ensure that the data have been captured and coded as specified in the procedures.

Following this initial processing, a series of detailed edits is applied to all diary data. Invalid responses are corrected or flagged for imputation. The final step is to assess whether the information reported in the diaries is of sufficient quality. This is done by comparing reported expenditures and the number of items with minimum thresholds estimated for each geographic area, household income class and household size. Diaries that satisfy the conditions are deemed usable, while those that do not are examined and deemed usable if there is a note that explains why the number and value of reported items are low. Diaries that do not meet the usability criteria are excluded from the estimates.

Imputation

Donor imputation through the nearest neighbour method is generally used to solve problems related to missing or invalid data from the electronic questionnaire. Data from one respondent (the donor) are used to impute missing or invalid data for another respondent with similar characteristics (the recipient). The imputation is done for one group of variables at a time; the groups are formed based on the relationship among the variables. The characteristics used to identify a donor are selected so that they are correlated with the variables to be imputed. Household income, dwelling type, and number of adults and children are commonly used characteristics. The household income amount used for imputation is taken from personal income tax data and equals the sum of the incomes of all household members aged 16 and over on December 31 of the calendar year preceding the survey.

Donor imputation is also used when information is missing from the daily expenditure diary. A respondent may have reported a particular expenditure item without including the cost, or a total amount spent (on groceries, for example) without listing the individual items. Imputation is also used to enhance the level of detail in the coding of reported items. For example, the information provided by the respondent may indicate that a bakery product was purchased, but a more detailed code is required to meet the survey's needs. In this case, donor imputation is used to impute the type of bakery product (e.g., bread, crackers, cookies, cakes and other pastries). Diary imputation is carried out at the reported item level, and the characteristics most often used to identify the donor are cost, available partial item code, household income and household size. Imputation is done by province and quarter to control for provincial differences and the seasonality of expenditures.

For personal income, respondents are matched to their records in the personal income tax data file. Missing or invalid tax data are generally donor imputed.

Income and expenditure imputation is performed primarily with Statistics Canada's Canadian Census Edit and Imputation System.

After imputation, taxes are added to the diary items that respondents were told to report without taxes. The applicable goods and services tax and provincial sales tax or the harmonized sales tax is added to these diary items according to the appropriate federal and provincial taxation rates for each good and service and for each month. For each survey reference period, research on tax rate changes is done to ensure that the appropriate rates are applied.

Estimation

The estimation of population characteristics from a sample survey is based on the premise that each sampled household represents a certain number of other households in addition to itself. This number is referred to as the survey weight, and the weighting process involves computing the weight assigned to each household. There are several steps in this process.

First, each household is given an initial weight that is equal to the inverse of its selection probability. A few adjustments are later applied to the questionnaire weights and the diary weights.

The questionnaire weights are first adjusted to account for the households that did not answer the questionnaire. They are then adjusted so that selected survey estimates agree with aggregates or estimates from independent auxiliary sources, such as population estimates and tax data.

The diary weights are also subject to a series of adjustments. A first factor adjusts for non-response to the questionnaire. A second factor compensates for households that respond to the questionnaire but refuse to complete the diary. The weights are also adjusted to demographic estimates in a manner similar to that used for the questionnaire. More information on the questionnaire and diary weights can be found in the User Guide for the Survey of Household Spending, 2023.

All questionnaire and diary expenditure variables are annualized. This is done by multiplying them by an appropriate factor based on their reference period. Some expenditure data are also corrected by another adjustment factor when they have been identified as "influential" or outlier values. For the diary, another adjustment is made to compensate for the non-responded days, i.e., days without any reported items and without a "No spending" mention.

For an expenditure category collected using the questionnaire, estimates are equal to the sum of the annualized, adjusted and weighted (using questionnaire weights) expenditures for that category. Estimates for an expenditure category derived from diary data are calculated in a similar manner, using diary weights and the appropriate annualization and adjustment factors. For expenditure categories that include data from both collection vehicles, estimates are based on the sum of estimates from the diary and from the questionnaire.

Weighted estimates are also subject to a review for the presence of influential values. These are weighted expenditure amounts for a given household and a given item that are much larger or smaller than the weighted amounts of other households for that same item in a given geographic area. Adjustments are made to the most extreme influential expenditure estimates.

Quality evaluation

When all processing and estimation steps are complete, the data are compared with the previous survey cycle's estimates and, when possible, with other data sources, such as the census, administrative sources and other Statistics Canada surveys.

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 respondents' information.

Suppression rules are applied to the various tables of SHS estimates to ensure respondent confidentiality.

Revisions and seasonal adjustment

The 2023 SHS estimates were computed with weights adjusted to 2023 population estimates. These population estimates are based on 2016 Census data, as well as more recent information from administrative sources such as birth, death and migration registers.

Data accuracy

The standard error is a common measure of sampling error. It is the degree of variation in the estimates attributable to the selection of one particular sample rather than another. Standard errors for the SHS are estimated using the bootstrap method. The coefficient of variation (CV) is the standard error expressed as a percentage of the estimate. SHS CVs are available for the national and provincial estimates, as well as for estimates by household type, age of reference person, income quintile, household tenure and size of area of residence. The CV at the national level for total household expenditures is 2.83% (only the 10 provinces are included).

Response rates
At the national level (10 provinces only), the response rate for the 2023 SHS questionnaire was 27.5%. The final diary response rate (defined as the percentage of usable diaries relative to the number of households in the sample) was 14.3%.

For the northern capitals, the response rate for Whitehorse was 27.2% for the questionnaire and 12.8% for the diary. Similarly, Yellowknife had a response rate of 26.9% for the questionnaire and 9.4% for the diary. For Iqaluit, the response rate was 48.1% for the questionnaire and 16.8% for the diary.

Non-sampling error
Non-sampling errors occur because certain factors make it difficult to obtain accurate responses and to ensure that these responses retain their accuracy throughout processing. Unlike sampling errors, non-sampling errors are not easily quantified. Four sources of non-sampling errors can be identified: coverage errors, response errors, non-response errors and processing errors. For more details about these errors, refer to the User Guide for the Survey of Household Spending, 2023.

Non-response bias
Non-response errors occur when potential respondents do not provide the required information or when the information they provide is unusable. The main impact of non-response on data quality is that it can cause a bias in the estimates if the characteristics of non-respondents differ from those of respondents in a way that impacts the expenditures studied. While non-response rates can be calculated, they provide only an indication of data quality, because they do not measure the degree of bias present in the estimates. The magnitude of non-response can be considered a simple indicator of the risks of bias in the estimates.

While the weights of respondent households are adjusted to compensate for non-respondent households, partial non-response, such as failure to answer some questions, is handled through imputation.

Documentation

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