Concepts, methodology and data quality

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This publication presents the results of the Sawmills survey. This survey measures, on a monthly basis, quantities of lumber produced and shipped by sawmills in Canada classified by the North American Industry Classification System (NAICS) to 321111. The target population for this survey includes all sawmills in Canada excluding Newfoundland and Prince Edward Island as identified by the Annual Survey of Manufactures and Logging (ASML).

General methodology

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

The sample includes approximately 275 of the largest sawmills in Canada.

Data are collected each month from survey respondents using a mail-out / mail-back process. Data capture and preliminary editing are performed simultaneously to ensure validity of the data. Businesses from whom no response has been received or whose data may contain errors are followed-up by telephone or fax.

Missing data for the current month are imputed automatically by applying to the previous month’s data, for the unit in question, the month-to-month change observed for the same period in the previous year. The only exceptions are the opening and closing stock values. Opening stocks are set equal to the value of the closing stocks from the previous month. Closing stocks are calculated by adding production quantities to opening stocks and then subtracting shipments and waste values. The option exists for the subject matter analyst to manually override these imputations with a better estimate based on pertinent knowledge about the industry or the business.

Final estimates of production, inventories and shipments by province are obtained by applying factors to the data collected in the monthly Sawmills survey. This process is called benchmarking. The benchmark factors are ratios of the total quantity of lumber produced by sawmills as measured by the ASML, to the total quantity of lumber produced by sawmills in the monthly Sawmills survey. These factors are calculated for each province, based on the latest ASML commodity data available.

Various confidentiality rules are applied to all data before they are released 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.

Direct disclosure could occur when the value in a tabulation cell is composed of a few respondents or when the cell is dominated by a few companies. Residual disclosure could occur when confidential information can be derived indirectly by piecing together information from different sources or data series.

Under normal circumstances, data are collected, captured, edited, tabulated and published within 6 to 8 weeks after the reference month.

Revisions

Once every year (normally in July), the monthly Sawmills series are revised. These revisions incorporate any data that may have been received after the close of the collection cycle during the previous reference year. In addition, the series are benchmarked to the most recent data from the ASML to correct for any under-coverage of sawmills activity in the monthly Sawmills survey.

Data Accuracy

Since monthly data for sawmills are benchmarked to the ASML data (census), the estimates are not subject to sampling errors. However, the results are still subject to the non-sampling errors associated with non-response, inaccurate reporting, and processing. Errors relating to non-response can be measured. All attempts are made to control inaccurate reporting and processing errors.

Moreover, survey results are analyzed to ensure comparability with patterns observed in the historical data series and the economic condition of the industry. Information available from other sources such as media, other government organizations and industry associations are also used in the validation process.

Non-response error

Some respondents may be unable to provide data for numerous reasons (i.e. fire, theft, strike, economic hardship, etc.), while others may be late in responding. To minimize non-response, delinquent respondents are followed up rigorously by phone or fax. Data for non-responding units are imputed using industry trend and other related information. Data are revised, usually once a year, at the same time as the new benchmark factors are produced to take into account questionnaires that have been received after the end of the monthly collection cycles since the previous revision.

Non-response error is calculated using the number of non-responses in the year divided by the number of total expected responses in the year for the units in the sample. The average non-response error for the Sawmills survey was estimated at 8% for 2005 (the last completed cycle).

This, however, is an imperfect indication of the extent of imputation since some portion of the data that goes into the calculation of the benchmark factors is also imputed.

Inaccurate response

Inaccuracy may result from poor questionnaire design or an inability on the part of respondents to provide the requested information or from misinterpretation of the survey questions. To reduce such errors the format and wording in the questionnaire are reviewed from time to time and modified based on feedback from survey respondents and data users. Respondents are also reminded of the importance of their contribution and of the accuracy of reported information.

Processing errors

These errors may occur at various stages in the processing of survey data such as data entry, verification, editing and tabulation. Data are examined for such errors using automated edits along with an analytical review by subject matter experts. Several checks are performed on the collected data to verify internal consistency and comparability over time.