Waste Management Industry Survey: Government Sector

Detailed information for 2010

The survey provides information on waste management financial and employment characteristics. It also collects information on collection, disposal and recycling quantities reported by municipalities and other public bodies that provide waste management services.

Data release - August 21, 2013

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

Description

The survey provides businesses, local governments, Environment Canada and various other public and private clients with comprehensive and comparable information on waste management financial and employment characterisitics. It also collects information on collection, disposal and recycling quantities reported by municipalities and other public bodies that provide waste management services.

Waste and recycling quantity data are combined with parallel data from the Waste Management Industry Survey: Business Sector (record no. 2009).

Reference period: Calendar year

Collection period: Fall and winter following the reference year

Subjects

• Environment
• Pollution and waste

Data sources and methodology

Target population

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.

Instrument design

The majority of the questions remain unchanged from cycle to cycle.

Sampling

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

Data are collected for all units of the target population, therefore, no sampling is done.

Data sources

Data collection for this reference period: 2011-11-01 to 2012-05-15

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Survey questionnaires were mailed to a total of 1 422 businesses and local governments. The responses were returned by mail. The questionnaires were addressed to a contact person who was either responsible for, or had knowledge of, the waste management operations of the survey unit. For businesses that had operations in more than one province, a separate questionnaire was completed for each province in which the waste management business operated. For example, a business with operations in three provinces completed three questionnaires, each one describing the activities within a province. This was not a concern for the local government survey.

Follow-ups by fax and/or telephone were carried out after the return due date to remind respondents to return their questionnaires.

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 is 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 local governments were very co-operative 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.

Historical data was used to fill in missing financial and employment values for the government sector survey. However due to the high response rate (87%) for this survey, very few values were in need of imputation.

Estimation

This methodology type does not apply to this statistical program.

Quality evaluation

One way to assess data accuracy is to compare it with data from other sources. For example, if the survey data indicates that the amount of waste disposed and diverted has risen substantially since the previous survey, one might also expect operating revenues and expenses to have risen. Similarly, if a provincial report is released indicating that the amount of diverted materials has increased significantly in that province, one might expect the data obtained from these surveys to follow the same trend. If the data did not follow the expected trends it would be investigated rigorously. One such comparison has been made with the business survey's financial data from 2010 against administrative data available on Statistics Canada's Business Register. In addition, recycling estimates were compared and validated with those published by the provincial governments of Nova Scotia and Ontario.

In addition to these comparisons, data are compared to 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 data which would divulge information obtained under the Statistics Act that relates to any identifiable person, business or organization without the prior knowledge or the consent in writing of that person, business or organization. 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 three years. For the most current data please refer to CANSIM tables 153-0041 to 153-0045.

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, extensive follow up and consultation with government departments and industry associations.