Monthly Survey of Manufacturing (MSM)
Detailed information for April 2016
The Monthly Survey of Manufacturing (MSM) publishes statistical series for manufacturers -- sales of goods manufactured, inventories, unfilled orders and new orders.
Data release - June 15, 2016
The MSM publishes the values (in Canadian dollars) of sales of goods manufactured, inventories and orders. The MSM data are used as indicators of the economic condition of manufacturing industries; as inputs to Canada's Gross Domestic Product; as components in the Statistics Canada (STC) composite indicator; as input to economic studies, and in econometric models (e.g. to determine market share, apparent domestic availability, etc.). Results from this survey are used by both the private and public sectors including finance departments of the federal and provincial governments, the Bank of Canada, Industry Canada, the System of National Accounts, the manufacturing community, consultants and research organizations in Canada, the United States and abroad, and the business press.
Reference period: Month
Data sources and methodology
The target population consists of all statistical establishments on the Business Register that are classified, according to the 2012 North American Industrial Classification System (NAICS), to the manufacturing sector.
In 1999, the Monthly Survey of Manufacturing (MSM) underwent an extensive redesign. A review of user requirements was first initiated. Then, with these requirements in hand, a survey was conducted in order to ascertain respondent's ability to report existing and new data. The study was also to confirm that respondents understood the definitions, which were being asked by survey analysts. The result of the concept review was a reduction of the number of questions for the survey from sixteen to seven. Most of the questions that were dropped had to do with the reporting of sales of goods manufactured for work that was partially completed.
This is a sample survey with a cross-sectional design.
Statistics Canada's Business Register provides the sampling frame for the MSM. The target population for the MSM consists of all statistical establishments on the Business Register that are classified to the manufacturing sector (by NAICS). The sampling frame for the MSM is determined from the target population after subtracting establishments that represent the bottom 5% of the total manufacturing sales of goods manufactured estimate for each province. These establishments were excluded from the frame so that the sample size could be reduced without significantly affecting quality.
The MSM sample is a probability sample comprised of approximately 10,500 establishments. A new sample was chosen in the autumn of 2012, followed by a six-month parallel run (from reference month September 2012 to reference month February 2013).
This marks the first process of refreshing the MSM sample since 2007. The objective of the process is to keep the sample frame as fresh and up-to date as possible. All establishments in the sample are refreshed to take into account changes in their value of sales of goods manufactured, the removal of dead units from the sample and some small units are rotated out of the GST-based portion of the sample, while others are rotated into the sample.
Prior to selection, the sampling frame is subdivided into industry-province cells. For the most part, NAICS codes were used. Depending upon the number of establishments within each cell, further subdivisions were made to group similar sized establishments' together (called stratum). An establishment's size was based on its most recently available annual sales of goods manufactured or sales value.
Each industry by province cell has a 'take-all' stratum composed of establishments sampled each month with certainty. This 'take-all' stratum is composed of establishments that are the largest statistical enterprises, and have the largest impact on estimates within a particular industry by province cell. These large statistical enterprises comprise 45% of the national manufacturing sales of goods manufactured estimates.
Each industry by province cell can have at most three 'take-some' strata. Not all establishments within these stratums need to be sampled with certainty. A random sample is drawn from the remaining strata. The responses from these sampled establishments are weighted according to the inverse of their probability of selection. In cells with take-some portion, a minimum sample of 10 was imposed to increase stability.
The take-none portion of the sample is now estimated from administrative data and as a result, 100% of the sample universe is covered. Estimation of the take-none portion also improved efficiency as a larger take-none portion was delineated and the sample could be used more efficiently on the smaller sampled portion of the frame.
Responding to this survey is mandatory.
Data are collected directly from survey respondents and extracted from administrative files.
Basic collection, data capture, preliminary edit and follow-up of non-respondents are primarily performed by staff in the Statistics Canada regional offices. Sampled companies are contacted either by mail or telephone, whichever they prefer. Data capture and preliminary editing are performed simultaneously to ensure the validity of the data. Companies from which no response has been received or whose data may contain errors are followed-up immediately.
Use of Administrative Data:
Managing response burden is an ongoing challenge for Statistics Canada. In an attempt to alleviate response burden, especially for small businesses, STC has been investigating various alternatives to survey taking. Administrative data files are a rich source of information for business data and STC is working at mining this rich data source to its full potential. As such, effective the August 2004 reference month, the MSM has reduced the number of simple establishments in the sample that are surveyed directly; some 2,500 units (representing over 20% of the MSM sample) will not be sent a questionnaire. Instead, MSM derives sales of goods manufactured data for these establishments from Goods and Services Tax (GST) files using a statistical model. The model accounts for the difference between sales of goods manufactured (reported to MSM) and sales (reported for GST purposes) as well as the time lag between the reference period of the survey and the reference period of the GST file. Inventories and unfilled orders estimates for establishments where sales of goods manufactured are GST-based are derived using the MSM's imputation system. The imputation system applies to the previous month values, the month-to-month and year-to-year changes in similar firms which are surveyed.
Detailed information on the methodology used for modeling sales of goods manufactured estimates derived from administrative data sources can be found in 'Monthly Survey of Manufacturing: Use of Administrative Data', which is available through the online catalogue number 31-533-XIE (free).
View the Questionnaire(s) and reporting guide(s) .
There are edits built into the data capture application which compare the captured data against unusual values, and check for logical inconsistencies. When an edit fails, the interviewer is prompted to correct the information (with the assistance of the respondent when necessary). For most edit failures the interviewer has the ability to override the edit failure if they cannot resolve the apparent discrepancy.
Both survey data and modeled data based on the GST are also subject to an extensive series of processing steps which thoroughly verify each record received. Edits are performed at a more aggregate level (industry by geographic level) to detect records which deviate from the expected range, either by exhibiting large month-to-month change, or differing significantly from the remaining establishments. All data which fail these edits are subject to manual inspection and possible corrective action.
Imputation is required for each characteristic in the constant sample panel for which no report has been received. Inventories and unfilled orders are also imputed for all records for which sales of goods manufactured are derived from GST records. These are calculated automatically, subject to certain constraints, by applying to previous month values the month-to-month and year-to-year changes in similar responding firms.
Estimates are produced based on returns from a sample of manufacturing establishments in combination with administrative data for a portion of the smallest establishments. The survey sample includes 100% coverage of the large manufacturing establishments in each industry by province, plus partial coverage of the medium and small-sized firms. Combined reports from multi-unit companies are pro-rated among their establishments and adjustments for progress billings reflect revenues received for work done on large item contracts. Approximately 2,500 of the sampled medium and small-sized establishments are not sent questionnaires, but instead their sales of goods manufactured are derived by using revenue from the GST files. The portion not represented through sampling -- the take-none portion - consist of establishments below specified thresholds in each province and industry. Sub-totals for this portion are also derived based on their revenues.
Industry values of sales of goods manufactured, inventories and unfilled orders are estimated by first weighting the survey responses, the values derived from the GST files and the imputations by the number of establishments each represents. The weighted estimates are then summed with the take-none portion. While sales of goods manufactured estimates are produced by province, no geographical detail is compiled for inventories and orders since many firms cannot report book values of these items monthly.
The new orders series by industry are derived by adding the change in unfilled orders over a period to sales of goods manufactured within that period.
The final data sets are subject to rigorous analysis that includes comparison to historical series and comparisons to other sources of data in order to put the economic changes in context. Information available from the media, other government organizations and economic think tanks is also used in the validation process.
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.
Confidentiality analysis includes the detection of possible direct disclosure, which occurs when the value in a tabulation cell is composed of a few respondents or when the cell is dominated by a few companies.
Revisions and seasonal adjustment
Monthly, preliminary estimates are provided for the reference month and revised estimates, based on late responses, are provided for the previous 3 months.
Up to and including 2003, the MSM was benchmarked to the Annual Survey of Manufactures and Logging (ASML). Benchmarking was the regular review of the MSM estimates in the context of the annual data provided by the ASML. Benchmarking re-aligned the annualized level of the MSM based on the latest verified annual data provided by the ASML.
Significant research by Statistics Canada in 2006-2007 was completed on whether the benchmark process should be maintained. The conclusion was that benchmarking of the MSM estimates to the ASML should be discontinued. With the refreshing of the MSM sample in 2007, it was determined that benchmarking would no longer be required (retroactive to 2004) because the MSM now accurately represented 100% of the sample universe. Data confrontation will continue between MSM and ASML to resolve potential discrepancies.
It is standard practice that every few years the sample is refreshed to ensure that the survey frame is up to date with births, deaths and other changes in the population. The refreshed sample is linked at the detailed level to prevent data breaks and to ensure the continuity of time series. It is designed to be more representative of the manufacturing industry at both the national and provincial levels.
In the interest of accurately interpreting the fundamental evolution of an economic phenomenon and producing forecasts of superior quality, Statistics Canada uses the X12-ARIMA seasonal adjustment method to seasonally adjust its time series. Trading-day weights and analysis of trends, levels and moving averages are updated and revised on an annual basis. This ensures that the data accurately reflect the latest developments in manufacturing.
While considerable efforts have been taken to ensure high standards throughout all stages of collection and processing, the resulting estimates are inevitably subject to a certain degree of non-sampling error. Non-sampling error is not related to sampling and may occur for various reasons. For example, non-response is an important source of non-sampling error. Population coverage, differences in the interpretations of questions and mistakes in recording, coding and processing data are other examples of non-sampling errors.
Non-sampling errors are controlled through a careful design of the questionnaire, the use of a minimal number of simple concepts and consistency checks. Measures such as response rates are used as indicators of the possible extent of non-sampling errors.
The MSM's average weighted response rate for collected sales of goods manufactured data is in the range of 94% to 98%. Table 2 in the 'Concepts, Definitions and Data Quality' document shows the weighted response, imputation and editing rates for collected data as well as for data based on the GST for the following five characteristics: sales of goods manufactured, raw materials and components inventories, goods / work in process inventories, finished goods manufactured inventories and unfilled orders.
Sampling error can be measured by the standard error (or standard deviation) of the estimate. The coefficient of variation (CV) is the estimated standard error percentage of the survey estimate. Estimates with smaller CVs are more reliable than estimates with larger CVs. Table 1 in the 'Concepts, Definitions and Data Quality' document shows the national level CVs for the following five characteristics: sales of goods manufactured, raw materials and components inventories, goods / work in process inventories, finished goods manufactured inventories and unfilled orders.
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