Biennial Waste Management Industry Survey

Detailed information for 2020

Status:

Active

Frequency:

Every 2 years

Record number:

2009

This survey collects information that will help Canadians understand the contributions the waste management industry makes to Canada's economy and environment.

Data release - Scheduled for October 3, 2022

Description

The survey provides comprehensive information about waste generated by Canadians, waste disposed and diverted from landfills, and their sources. This information is collected from businesses that provide waste management services.

This data is used by local governments, Environment Canada and various other public and private clients.

Reference period: Fiscal year

Collection period: Spring and summer following the reference year

Subjects

  • Environment
  • Pollution and waste

Data sources and methodology

Target population

IN-SCOPE WASTE MANAGEMENT BUSINESSES SECTOR
The target population includes all firms operating in Canada that provide waste management services.

The survey frame was based on information from the previous survey, supplemented and updated with information from the Statistics Canada Business Register (BR) and industry directories. Firms selected from the BR are a subset of Waste management and remediation services, North American Industry Classification System (NAICS) 562.

The following NAICS classifications are considered to be "in scope" for the Waste Management Industry Survey: Business Sector: 56211, Waste collection; 56221, Waste treatment and disposal; and 56292, Material recovery facilities.

IN-SCOPE LOCAL GOVERNMENTS THAT PROVIDE OR MAKE PROVISION FOR WASTE MANAGEMENT SERVICES
The target population for this survey of waste management practices includes all large municipalities (population of 5,000 or more), or waste management commissions or boards representing municipalities.

IN-SCOPE RETAILERS AND OTHER ORGANIZATIONS THAT PARTICIPATE IN DIVERSION PROGRAMS OUTSIDE THE WASTE MANAGEMENT STREAM
The following NAICS classifications are considered to be "in scope".

4142, Home entertainment equipment and household appliance merchant wholesalers; 4181, Recyclable material merchant wholesalers; 4182, Paper, paper product and disposable plastic product merchant wholesalers; 442, Furniture and home furnishings stores; 443, Electronics and appliance stores; 445, Food and beverage stores; 452, General merchandise stores.

Instrument design

The majority of the questions remain unchanged from cycle to cycle. In 2020, new questions were added to capture specific information related to non-traditional waste management streams.

Sampling

IN-SCOPE WASTE MANAGEMENT BUSINESSES SECTOR
This is a census with a revenue cut-off.

IN-SCOPE LOCAL GOVERNMENTS THAT PROVIDE OR MAKE PROVISION FOR WASTE MANAGEMENT SERVICES
This is a census with a population cut-off.

IN-SCOPE RETAILERS AND OTHER ORGANIZATIONS THAT PARTICIPATE IN DIVERSION PROGRAMS OUTSIDE THE WASTE MANAGEMENT STREAM
This is a sample survey with a cross-sectional design.

The Generic Survey Universe File is used as the survey frame.

A stratified sample of establishments classified to the 4-digit level of the NAICS Canada 2017 and to geographical regions was selected. Respondents from reference year 2018 who were in-scope and a list of establishments provided by subject matter were selected with certainty.

Data sources

Data collection for this reference period: 2021-06-07 to 2021-12-08

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Data are collected directly from survey respondents and alternate data sources.

Data are collected using an electronic questionnaire. Respondents are emailed invitation letters and Secure Access Code letters. A letter explaining the purpose of the survey, the requested return date and the legal requirements of response are included as a package in the email invitation.

Follow-up procedures are applied when a questionnaire has not been received after a pre-specified period of time. Note that the questionnaire is available in both English and French versions.

Employment and financial data was imputed for small firms that were not surveyed as well as in-scope firms that did not respond. Administrative sources such as the Statistics Canada Business Register and tax records were used to fill in the missing values.

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

Error detection

Many factors affect the accuracy of data produced in a survey. For example, respondents may have made errors in interpreting questions, answers may have been incorrectly entered on the questionnaires, and errors may have been introduced during the data capture or tabulation process. Every effort was made to reduce the occurrence of such errors in the survey. These efforts included: a complete verification of keyed data, validity and consistency edits, extensive follow-up with the large businesses, and consultation with selected government departments and industry associations.

Imputation

Although most businesses and local governments cooperated in answering the survey, some could not provide all the data required in the form in which it was requested. In cases where values were missing from survey cells or where the respondent did not complete a questionnaire even after extensive follow-up, information was imputed.

For larger firms and local governments, the imputed values were compared with values from previous years and other sources, such as annual reports and filings with the provincial authorities for local governments, to ensure that the high quality of imputed values.

Estimation

This methodology is used for the retailers and other organizations module. It is not applied to the local government and business sectors.

The Generalized Estimation System developed at Statistics Canada is used to produce domain estimates and quality indicators. It is an SAS-based application for producing area-level estimates for a population based on a sample.

An initial sampling weight (the design weight) is calculated for each unit in the survey and is the inverse of the probability of selection. The weight calculated for each sampling unit indicates how many other units it represents. Sampling units that are selected with certainty (must-take units) have sampling weights of one and represent only themselves. Outlier units with larger than expected sizes are considered misclassified and their weights are usually adjusted to represent only themselves. The weights of other units are adjusted accordingly to account for the existence of outliers. The final weights are usually either one or greater than one. Sampling error was measured by the coefficient of variation (CV), which represents the proportion of the estimate that comes from its associated variability. CVs were calculated and are indicated in the data tables.

Quality evaluation

One way to assess data accuracy is to compare it with data from other sources. For example, if the survey data indicate that the amount of waste disposed and diverted has risen substantially since the previous survey, operating revenues and expenses can also be expected to have risen. Similarly, if a provincial report is released indicating that the amount of diverted materials has increased significantly in that province, the data obtained from these surveys can be expected to follow the same trend. If the data did not follow the expected trends, it was investigated rigorously.

In addition, data are compared with those published by other organizations, such as provincial governments and cities. If there are significant differences between the different sets of comparable data, these must be accounted for and explained. This also applies to cases where there are large positive or negative changes in the data values from cycle to cycle.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects under the Statistics Act that could identify any person, business or organization, unless written consent of that person, business or organization has been given. 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.

An intensive peer review of all tabular data is conducted prior to publication. This manual verification ensures that both inter- and intra-tabular comparisons cannot be made that may lead to disclosure of confidential data.

Revisions and seasonal adjustment

Revisions are made for the previous survey reference period with the initial release of the current data, as required. The purpose is to address any significant issues with the data that were found between survey cycles. The actual period of revision depends on the nature of the issue, but rarely exceeds four years, or two survey cycles. For the most current data, please refer to tables 38-10-0032, 38-10-0035, 38-10-0036 and 38-10-0138.

Data accuracy

The accuracy of data collected in a census survey is affected by non-sampling error. Examples of non-sampling error include coverage error, data response error, non-response error and processing errors. Every effort is made to reduce these types of errors, including verification of keyed data, consistency and validity edits, and extensive follow-up and consultation with government departments and industry associations.

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