Survey of Household Spending (SHS)

Detailed information for 2015





Record number:


The main purpose of the survey is to obtain detailed information about household spending as well as limited information on dwelling characteristics and household equipment.

Data release - January 27, 2017


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, certain dwelling characteristics (e.g., type, age and tenure) and certain information on household equipment (e.g., electronics and communications equipment). The survey is conducted annually in the 10 provinces and usually every other year in the territories.

The SHS combines a questionnaire with recall periods based on the type of expenditure (1, 3 or 12 months, last payment, four weeks) and an expenditure diary that selected households complete for two weeks following the interview. As well, data collection is continuous throughout the year.

The survey adjusts collection methods and reference periods to accommodate respondents' ability to provide accurate information. In general, longer reference periods are used for goods and services that are more expensive or purchased infrequently or irregularly. On the contrary, shorter reference periods are used for goods and services that are of less value or purchased frequently or at regular intervals.

SHS data are used at Statistics Canada by the System of National Accounts, in particular as input to calculate the gross domestic product (GDP). The data also helps to update the basket weights of the Consumer Price Index (CPI). In addition, many federal and provincial government departments and ministries use the data to develop social and economic policies and programs. Various groups use them to address issues 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 twelve monthly collection cycles.


  • 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 the population of Canada's 10 provinces, excluding residents of institutions, members of the Canadian Forces living in military camps and people living on Indian reserves. In all, these exclusions make up about 2% of the population.

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. Also excluded, in addition to people living in institutions, are people living in other types of collective dwellings:

- people living in residences for dependent seniors; and
- people living permanently in school residences, work camps, etc.; and
- members of religious and other communal colonies.

Collection 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 (see the section on estimation).

Instrument design

Since 2010 in the provinces and 2015 in the three territorial capitals, the SHS combines the use of a questionnaire and an expenditure diary. The questionnaire is used for the most part to collect regular and less frequent expenses during a computer assisted personal interview. The diary is used to collect frequent or smaller expenses, which are difficult to recall during a retrospective interview.

In order to introduce this new collection model, each of the many expenditure items to be collected by the SHS was assigned a collection mode in advance, which was either the questionnaire or the diary. For the questionnaire items, a reference period of one, three or twelve months, last payment, or four weeks, was also selected. Those choices were largely based on the results of qualitative tests, on the international expertise in that type of collection model and on the studies conducted to gauge the potential increase in the variances of estimates due to shortening of reference periods. These studies were based on the data from the Consumer Expenditure Survey conducted by the U.S. Bureau of Labor Statistics.

The content of the questionnaire was determined in consultation with the primary internal and external users of the survey data.


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

In the ten provinces, the sampling unit in the first stage is the geographic area (referred to as a cluster). In the second stage, the sampling unit is the dwelling.

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

Sample design in the ten provinces:

A stratified multi-stage sampling design was used to select the sample in the ten provinces. It is essentially a two-stage design, of which the first stage is a sample of geographic areas (referred to as 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 a number of components of the Labour Force Survey's (LFS) sample design to minimize operating costs, though the dwellings selected for the SHS are different than those selected for the LFS.

Since the 2012 SHS, the selection of households to complete the diary was done such that fifty percent of households selected for the interview were asked to fill out a diary. Thus, in each selected cluster, a subsample of previously chosen households fill out the diary. The 2015 SHS design was modified so that one hundred percent of households that were sampled for the interview between August and December were also selected to complete the diary, while the rate remained at fifty percent in the first part of the year.

The national sample is first divided among the provinces on the basis of 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. Provincial sample sizes are shown in Table 1a of Section 4 of the SHS User Guide for the Survey of Household Spending, 2015, which is now available as part of the Household Expenditures Research Paper Series (62F0026M)). The sample is then divided into strata defined by grouping clusters with similar characteristics based on a number of socio-demographic variables. Some strata were 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.

Sample design in the territories:

A one-stage sampling design was used to select the sample in the three territorial capitals. The first step of the sample allocation was to determine the number of dwellings to be sampled in each city. The overall sample was allocated to each city by taking into account the size of the city and the quality of the estimates obtained from previous cycles of the SHS in the North. The sample sizes for the territorial capitals are shown in Table 1b of Section 4 of the User Guide for the Survey of Household Spending, 2015, which is now available as part of the Household Expenditures Research Paper Series (62F0026M)).

In the territorial capitals, all households sampled for the interview are also selected to complete an expenditure diary.

The sample of the 2015 Survey of Household Spending consists of 17,603 households throughout the ten provinces and 767 households in the three capitals Whitehorse, Yellowknife and Iqaluit.

Since data are collected monthly, the sample is divided into 12 subsamples of similar size. During that process, the SHS sample is coordinated with the samples of the LFS and, to a lesser extent, the Canadian Community Health Survey (CCHS), which use the same sampling frame and conduct personal interviews for part of their sample. Coordination means that, wherever possible, if a cluster is selected for more than one survey, collection for the surveys will take place in the same month. This will enable the interviewer to become familiar with the neighbourhood, collect the data and carry out the necessary follow-up for more than one survey at a time.

Data sources

Data collection for this reference period: 2015-01-02 to 2015-12-31

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

The data are mostly obtained directly from the respondent through two collection modes: a personal interview conducted by an interviewer using a questionnaire on a laptop, and a diary in which the household is required to report its daily expenditures over a two-week period. The data were collected on a continuous basis from January to December of the survey year from a sample of households spread over 12 monthly collection cycles.

Firstly, households in the sample are asked to respond to a questionnaire (administered using a computer-assisted personal interview) that 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 covered are typically collected. For other types of expenditures collected in the interview, recall periods of one month, three months or twelve months are used. The recall periods are defined in terms of 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. Demographic characteristics, dwelling characteristics and household equipment information, which are also collected in the interview, refer to the household's situation at the time of the interview. Starting in 2013, respondents are informed that the survey data will be combined with tax data to obtain selected variables related to personal income for household members aged 16 and over on December 31 of the calendar year preceding the survey year. The reference period for personal income tax data is the calendar year prior to the survey year.

Following the interview, respondents selected to complete the expenditure diary are asked to record the expenditures of all household members for a period of two weeks starting the day after the interview. Households are required to include all of their spending, except for a few types of expenditures, such as rent, regular utilities payments, and real estate and vehicle purchases. Households have the option of providing receipts of their purchases made during the two-week period in order to reduce the amount of information manually recorded in the diary. However, they are asked to write out additional information on the receipt if the description of the item appearing on the receipt is incomplete.

A telephone follow-up is carried out a few days after the interview to address any questions the respondent may have about the diary and to reiterate important information about how to complete it. At the end of the two-week period, the interviewer returns to the respondent's residence to pick up the diary and ask a few additional questions to help the respondent report expenditures that he or she may have forgotten.

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 T1 income tax information from Canada Revenue Agency (CRA) to household members. The linking is only done for individuals aged 16 and over on December 31st of the calendar year preceding the survey, who granted permission for their tax information to be linked to their survey responses. Income is imputed for individuals who do not grant permission as well as those for which a linkage to T1 information was not successful.

The SHS links T1 income tax data to survey respondents through exact and probabilistic matching record linkage techniques.

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

Error detection

The computerized questionnaire contains many features designed to maximize the quality of the data collected. Many edits are built into the questionnaire to compare the reported data with unusual values and detect logical inconsistencies. When an edit fails, the interviewer is prompted to correct the information (with the respondent's help, if necessary). Once the data are transmitted to Head Office, a comprehensive series of processing steps is undertaken for the purpose of detailed verification of each questionnaire. Invalid responses are corrected or flagged for imputation.

A number of edits are also carried out on the diary data when the diaries are received at Head Office and throughout the capture and coding steps. 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 items that appear in both the data recorded in the diary and the receipts provided by the respondent. After validation, capture and coding, quality control procedures are applied. A sample of diaries is selected and completely rechecked to ensure that the diaries were captured and coded as specified in the procedures.

Then a series of detailed edits are performed on all diaries. 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 using parameters which differ according to the household characteristics. The reported expenditures and number of items are compared with minimum thresholds estimated for each geographic area (Atlantic Provinces, Quebec, Ontario, Prairie Provinces, British Columbia, and the three territorial capitals combined), each household income class and each household size. Diaries that satisfy the conditions are deemed usable. The other diaries are examined. They will be deemed usable if there is a note explaining their low expenditures or their small number of reported items. Diaries that do not meet the usability criteria are treated the same as non-response diaries; they are excluded from the estimates.


To solve problems of missing or invalid information in interview questions, donor imputation by the nearest neighbour method is generally used. Data from another respondent with similar characteristics (the donor) are used to impute. The imputation is done on one group of variables at a time, with the groups formed on the basis of the relationships among the variables. The characteristics used to identify the donor are selected such that they are correlated with the variables to be imputed. Household income, dwelling type and number of adults and children are commonly used characteristics. For operational reasons, the income information from personal income tax data is not available in time for imputation of the survey data. Consequently, the household income used for imputation is taken from an additional question on personal income that is asked during the interview exclusively for the purpose of data imputation. The incomes of all household members aged 16 and over on December 31st of the calendar year preceding the survey are summed to derive household income.

Donor imputation is also used when information is missing from the daily expenditure diary. A respondent may have reported a particular expenditure item without its cost or given the total amount spent (on groceries, for example) without listing the individual items. Imputation is also used to enhance the level of detail in coding the items reported. For example, the information provided by the respondent may simply 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 (bread, crackers, cookies, cakes and other pastries, etc.). Diary imputation is carried out at the reported item level, and the characteristics most often used to identify the donor are cost, available partial code, household income and household size. Imputation is done by province and quarter to control for provincial differences and seasonality of expenditures.

For personal income, people are matched to 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 (CANCEIS).

After imputation, taxes are added to those diary items that should be reported with taxes excluded. In order to reduce the response burden, instructions are provided to the respondents indicating when to include or exclude taxes from reported expenses. Thus, the Goods and Services Tax (GST) and the Provincial Sales Tax (PST), or the Harmonized Sales Tax (HST) are added to the diary items, according to the appropriate federal and provincial taxation rates.


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 a number of steps in that process.

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

The interview weights are first adjusted to take into account 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 (for more information refer to section 3.6 of the User Guide for the Survey of Household Spending, 2015, which is now available as part of the Household Expenditures Research Paper Series (62F0026M)).

The diary weights are also subject to a series of adjustments. A first factor adjusts for the nonresponse 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 interview (for more information refer to section 3.6 of the User Guide for the Survey of Household Spending, 2015, which is now available as part of the Household Expenditures Research Paper Series (62F0026M)).

All interview and diary expenditure variables are annualized: they are multiplied by an appropriate factor based on the reference period. Some expenditure data are also corrected by another adjustment factor when influential values are identified. For the diary, another adjustment is made to compensate for the non-responded days.

The estimates for a given expenditure category collected from the interview are therefore the weighted sums (using interview weights) of the annualized and adjusted amounts. The estimates of an expenditure category derived from diary data are calculated in a similar manner using diary weights and the appropriate annualisation and adjustment factors. Lastly, summary expenditure category estimates that include components from both collection methods are produced by taking the sum of the estimates of the diary and the interview components.

Quality evaluation

When all processing and estimation steps are complete, the data are compared with the previous year'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 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.

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

Revisions and seasonal adjustment

A new methodology which combines a questionnaire and a diary to collect the household expenditures was introduced for the 2010 survey. The reference periods have been reduced for many expenditure items and collection is continuous throughout the year. Although the expenditure data collected since 2010 are similar to those of previous years, the changes to data collection, processing and estimation methods have created a break in the data series. As a result, caution should be used in comparing SHS data since 2010 with previous years, unless otherwise noted.

From time to time, revisions to past estimates may be necessary for enhancements related to new data sources, estimation methods and expenditure classifications.

The 2015 SHS estimates were computed with weights adjusted to 2015 population estimates. These population estimates are based on 2011 Census data as well as more recent information from administrative sources such as birth, death and migration registers.

SHS estimates for the years 2010 to 2013 were previously based on weights calibrated to population estimates produced using data from the 2006 Census. In order to make SHS estimates comparable over time, the 2010, 2011, 2012, and 2013 SHS estimates have been revised using the population projections based on the 2011 Census. The entire weighting process is thus standardized for the years 2010 to 2015.

SHS estimates prior to 2010 (2001-2009) are based on weights calibrated to population estimates produced using data from the 2001 Census. There is no plan to revise these estimates (using 2006 or 2011 Census data) due to the break in the data series starting with the 2010 SHS.

No historical revisions were made for the estimates in the three territorial capitals since 2015 is the first time data is collected in these cities using the new design of SHS.

Data accuracy

The standard error is a common measure of sampling error. It is the degree of variation in the estimates due to the selection of one particular sample rather than another. The 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 the 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 0.8%.

For the ten provinces altogether, the response rate for the 2015 SHS interview is 60.9%. The diary response rate among the interview-respondent households who were selected to fill out a diary is 65.7%. The final diary response rate (defined as the percentage of usable diaries relative to the number of households selected to fill out the diary) is 39.9%.

For the three territorial capitals altogether, the interview response rate is 65.8% for the 2015 SHS. In the three territorial capitals, all households selected for the interview are also selected to fill out a diary. The diary response rate is 38.6%.

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 error can be identified: coverage error, response error, non-response error and processing error.

Errors due to non-response 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, since 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.


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