Waste Management Industry Survey: Government Sector

Detailed information for 2000

The survey provides 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.

Data release - April 25, 2002

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

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

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. However, a module of questions that are of specific interest to Statistics Canada is introduced on a one-time basis each cycle. Before these questions are incorporated into the final version of the questionnaire, they are reviewed internally and by industry experts external to Statistics Canada.

Sampling

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

This methodology does not apply.

Data sources

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

Questionnaires were mailed to respondents in January and telephone and mail follow-ups were conducted thereafter.

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

Programs written in MS FoxPro are used to impute missing financial and employment cells. Donor records are identified from valid and complete responses and missing values are imputed from these donor records. For missing waste and recyclable quantity values, historical data are used to impute for the current cycle. Where no historical data exist or they are incomplete, administrative data obtained from provincial/territorial and other sources are used.

Estimation

This methodology type does not apply to this statistical program.

Quality evaluation

One way to assess data quality is to compare it to the trends of other data collected. For example, comparing the waste statistics for 2000 with those for 1998, it is apparent that there has been substantial growth in the Canadian waste management industry. On a per capita basis, more non-hazardous waste was disposed and prepared for recycling during 2000 than in 1998. As would be expected, the upward trends seen in the waste quantity estimates are reflected in the financial and employment estimates of the business and government sectors of the industry.

Comparing the waste data with known economic trends is another way of validating the data. Economic growth is one indicator of the general state of the economy. Positive growth indicates an active economy: more money spent on goods and services contribute to an increase in waste production.

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 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 identifiable data.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

This methodology does not apply to this survey.