Manufacturing and Energy Division

Net Cash Expenditures Statement

Important:

Statistics Canada has replaced the previous Schedule II “Non-Capital Repair and Maintenance Expenditures” with a new Schedule VII “Non-Conventional Sector” to include a detailed account of i) Machinery and ii) Capital Construction (building and engineering) for the non-conventional sector.

Helpful Hints to Completing this Questionnaire:

The total value of sales reported in Schedule V must equal the value entered in Schedule I, item #1.

The total royalties as reported in Schedule II, “Non-Conventional Sector” (if applicable), items #14 and #15 and Schedule III, “Conventional Sector Operating Costs and Royalties”, items #6, #7, #8 must equal the value entered in Schedule I, item #4.

Total operating costs as reported in Schedule II, “Non-Conventional Sector”, item #13 (if applicable) and Schedule III, “Conventional Sector Operating Costs and Royalties”, item #5 must equal the value entered in Schedule I, item #5.

Table of Contents

Schedule I – Revenues, Expenses and Net Income
Schedule II – Non-Conventional Sector
Schedule III – Conventional Sector Operating Costs and Royalties
Schedule IV – Upstream Expenditures – Conventional Area (Both Capitalised and Expensed)
Schedule V – Volume and Value of Sales
Schedule VI – Balance Sheet
Schedule VII – Non-Conventional Sector

Schedule I - Revenues, Expenses and Net Income

  1. Sales before Royalties, Taxes and Other Charges: Report the sales or transfer value of produced goods or services before any adjustment or intersegment elimination. Please include royalties and taxes that are imposed at the time of sale. Exclude G.S.T.
  2. All Other Revenues: Include cash revenue items not reported elsewhere such as dividend receipts, rentals, overhead and processing revenue received as operator and /or owner of facilities. Such processing revenues should be reported gross.
  3. Gross Revenues: The sum of lines 1 and 2.
  4. Royalties and Similar Payments: The sum of Schedule II, lines 14 and 15 and Schedule III, lines 6, 7, and 8.
  5. Operating Costs: Please include cost of materials and supplies used in production, surface lease rentals, lifting costs and all other expenditures which are related to producing operations. Exclude any ‘non-cash’ charges and royalties. All general and administrative costs related to producing activities and charged to current year operations should also be included here.
  6. Salaries and Wages: Include the cost of salaries and wages (including bonuses and commissions, employer contributions to pension, medical, unemployment insurance plans, etc. ) paid to your own workforce during the reporting period.
  7. Other Cash Operating Costs: Include only costs associated with non-producing operations and other expense items not reported elsewhere.
  8. Interest Expense: Include interest paid on bank loans, bonds, etc.
  9. Federal Income Tax: Include federal income tax pertaining to the current period and assumed to be currently due.
  10. Provincial Income Tax: Include provincial income tax pertaining to the current period and assumed to be currently due. The amount reported should include the Saskatchewan Corporate Capital Tax Surcharge if applicable.
  11. Deferred Income Tax: Include accrued tax obligations reflected as an expense in the income statement, but not payable in the current reporting period.
  12. Exploration and Development Expenses Charged to Current Operations: Include exploration and development expenses charged to current operations.
  13. Depreciation/Amortization: The systematic charge-off to expense of costs for depreciable assets that had been initially capitalised or deferred. Write-downs of depreciable assets resulting from impairments should be included in this category. However, write-offs arising from unusual dispositions and gains/losses on sales of assets should be reported in lines 15 and 16 respectively.
  14. Depletion: Include the current depletion charges for costs subject to such deduction. Write-offs resulting from the application of ceiling tests should be reported in line 15, “Write-offs and amortization of deferred charges”. Gains and losses on disposal of properties should be reported in line 16, “Other non-cash items”.
  15. Write-offs and Amortization of Deferred Charges: Adjustments may be made for non-operating items which the company ordinarily eliminates from its reported “Internal cash flow”.
  16. Other Non-cash Items: Include non-cash items not reported elsewhere such as unrealised losses on currency transactions, non-controlling shareholders’ interest in earnings of consolidated subsidiaries, and the equity portion of losses of unconsolidated affiliates. This item should be reduced by such non-cash revenue items as unrealised currency gains, non-controlling shareholders’ interest in losses of consolidated subsidiaries, and equity in earnings of unconsolidated affiliates.
  17. Total Operating Cost: The sum of lines 4 to 16.
  18. Net Income: Line 3 minus line 17.

Schedule II - Non-Conventional Sector

*The Non-Conventional Sector relates to operations as defined in the A.E.U.B. Publication Alberta Active Projects - Oil Sands and Heavy Oil Schemes (Catalogue A.E.U.B. ST-97-44). Effectively, these operations take place in the geographical areas of Cold Lake, Peace River, Athabasca, Wabasca and Lindbergh, etc.

Regarding partnerships and joint venture activities or projects, report the expenditures reflecting your company’s net interest in such oil sands projects or ventures.

  1. Land and Lease Acquisition and Retention:
    a) Acquisition costs, oil rights fees and retention costs.
    b) Cost of land and lease purchased from others.
  2. Machinery and Equipment: Include items such as boilers, compressors, motors, pumps and any other items that may be termed manufacturing or mining equipment as opposed to a fixed installation such as a building.
  3. Housing: Value of residential structures and related infrastructure within a company townsite.
  4. Drilling Expenditures and Pre-Mining Costs: Drilling expenditures include core hole and delineation drilling. Include the cost of casing and other materials and equipment left in place, core analysis, logging, road building, and other directly related services. Pre-mining costs include overburden removal and other pre-production expenditures.
  5. Capitalized Overhead: Report the cost of capitalized overhead not allocated above. These overhead charges should exclude any amounts reported on Schedule III or Schedule IV.
  6. Total: The addition of lines 1 to 6.
  7. Field, Well and/or Plant: Include all direct operating expenses and any other expenses directly related to the mining, stimulation, processing, upgrading and delivery of the product, and cost of purchased fuel and electricity
  8. Taxes (excluding income taxes and royalties): Include taxes to federal, provincial and municipal governments, but exclude royalties, income taxes, and taxes that are part of the list price of purchases.
  9. Cost of Purchased Fuel and electricity: For crude oil operations only, include costs for fuel and electricity for all sites.
  10. Operating Overhead: Include all remaining general and administrative expenses related to upstream operations, including any corporate allocation to this segment. (These overhead charges should exclude any reported under Capitalised overhead, line 5 above).
  11. Total Operating Costs: The summation of lines 8 to 12.
  12. Provincial Royalties: Include all monies payable to provincial governments based on production.

Schedule III – Conventional Sector Operating Costs and Royalties

Operating costs include all direct operating expenses such as wages and salaries, materials and supplies, fuel and power, well conditioning costs, municipal taxes, other direct operating expenses, maintenance and repairs expensed and contract services. Also include the non-capitalised cost of purchased injection materials used in enhanced recovery projects.

  1. Field, Well and Gathering Operations - Oil and Gas: Include primary, secondary, and tertiary recovery and pressure maintenance facilities, gathering systems and other well site facilities, surface lease rentals, and cost of purchased fuel and electricity.
  2. Natural Gas Processing Plants: Include expenses associated with field processing plants as well as reprocessing activities, recycling projects, and cost of purchased fuel and electricity.
  3. Taxes (excluding income taxes and royalties): Include taxes to federal, provincial and municipal governments, but exclude royalties, income taxes, and taxes that are part of the list price of purchases
  4. Operating Overhead: Include all remaining general and administrative expenses related to upstream operations, including any corporate allocation to this segment. (These overhead charges should exclude any reported on Schedule IV).
  5. Total Operating Costs: The addition of lines 1 to 4.
  6. Federal Crown Royalties: Are amounts paid to the federal government, but excluding Indian lands royalties.
  7. Provincial Royalties and Taxes: Are amounts paid during the reporting period for royalty or royalty-like levies. In Alberta, include the “freehold mineral tax” together with the standard crown royalties on conventional oil and gas production. In Saskatchewan, include the standard crown royalties on oil and gas production plus the “freehold production tax”. In Manitoba, include the standard crown royalties and “freehold taxes” collected by the Manitoba government.
  8. Non-Crown Royalties and Similar Payments:
    a) Indian lands royalties: are amounts paid to Indian bands, either directly or indirectly, based on the level of production.
    b) Freehold royalties: are royalties that have been paid to parties, other than the Crown, who own the mineral interest to the property.
    c) Overriding royalties: are payments (normally free of all costs of development and operation) arising from an economic interest in a property.

Schedule IV - Upstream Expenditures - Conventional Area (Both Capitalised and Expensed)

  1. Oil and Gas Right Acquisition and Retention Costs: (excluding inter-company sales or transfers) includes:
    a) Acquisition costs and fees for oil and gas rights (include bonuses, legal fees and filing fees).
    b) Oil and gas rights retention costs.
  2. Cost of Land and Lease Purchased from Other Petroleum Companies: Purchases from companies that are engaged primarily in petroleum activities.
  3. Geological and Geophysical: Include such activities as seismic crew expenses, both company owned and contract. Include camp, bulldozing and dirt work, flying crews in and out, seismograph, velocity survey, gravity meter, magnetometer, core drilling, photo geological digital processing, magnetic playback and bottom hole contributions and environmental impact studies and other similar pre-exploration expenditures. All seismic or geological and geophysical expenditures (including stratigraphic tests) should be reported here, whether such activity is deemed exploration or development by the company.
  4. Exploration Drilling: Drilling outside a proven area or within a proven area but to a previously untested horizon, in order to determine whether oil or gas reserves exist rather than to develop proven reserves discovered by previous drilling. Include costs of dry wells, casing and other materials and equipment abandoned in place, productive wells, including capped wells, and wells still in progress at year-end. Include, also, costs incurred in fighting blow-outs, runaways, and in replacing damaged equipment.
  5. Total Exploration Spending: Addition of lines 1 to 4. Should be reported gross (whether capitalized or expensed) before deducting any incentive grants. Related overhead should be included in line 14 below.
  6. Development Drilling: Drilling within the proven area of an oil or gas reservoir to the depth of a stratigraphic horizon known to be productive for the purpose of extracting oil or gas reserves. This will cover costs of dry wells, including casing and other materials and equipment abandoned in place; productive wells, including capped well; and wells still in progress at year end. Include, also, costs incurred in fighting blow-outs, runaways, and in replacing damaged equipment. Exclude costs associated with service wells.
    Note: There should be no development expenditures until a development plan has been approved.
  7. Cost of Proven Reserves Purchased: Purchases from those companies that are engaged primarily in petroleum activities.
  8. Total Development Spending: Should be reported gross (whether capitalized or expensed) before deducting any incentive grant. Related overhead should be included in line 16 below.
  9. Production Facilities: Include tangible well and lease equipment comprising casing, tubing, wellheads, pumps, flowlines, separators, treaters, dehydrators. Include gathering pipelines, lease and centralized tank batteries and associated facilities prior to delivery to trunk pipelines terminals, and other production facilities. Include, also, costs associated with intangibles such as pre-production studies costs, and those expenditures that you consider to be pre-development.
  10. Non-Production Facilities: Include automotive, aeroplane, communication, office and miscellaneous equipment not otherwise provided.
  11. Enhanced Recovery Projects: Include only expenditures on facilities in tertiary projects involving steam injection, miscible flooding, etc. Include service wells, both tangible and intangible, including the costs of drilling and equipping injection wells and also the cost of capitalized injection fuel (miscible fluid) costs, but exclude non-recoverable injection fluids charged to current operations.
  12. Natural Gas Processing Plants: Report only the capitalized amounts of the plants, including structures, measuring, regulating and related equipment.
  13. Drilling Rigs and Supply Boats: Report expenditures including progress payments for the purchase of new and imported used and new drilling rigs (on and offshore) and supply boats.
  14. Total Production Spending: Addition of lines 9 to 13. This should be reported gross before deducting incentive grants. Related overhead should be included in line 17 below.

Upstream Overhead

Allocate capitalized upstream overhead to the categories indicated (lines 15 to 17). These overhead charges should exclude any reported on Schedule III.

Schedule V - Volume and Value of Sales

Exclude oil and gas purchased for resale, refining, fractionating or further processing, but include value and volume of royalty portion of production.

  1. Conventional crude oil and condensate: Includes field production of conventional light and heavy crude oil and condensate that is subject to old or new oil royalty rate.
  2. Synthetic crude oil: Synthetic crude oil obtained by the upgrading of crude bitumen or by the modification of coal or other materials should be reported here.
  3. Crude Bitumen: Crude Bitumen, in its naturally occurring viscous state, will not flow to a well.
  4. Marketable natural gas: Report here the volume of natural gas production equal to gross new production from natural reservoirs, less injected and stored, processing shrinkage, plus or minus statistical adjustment, less field disposition and uses, field flared and waste, gathering system disposition and uses, reprocessing flared and reprocessing fuel, and other disposition and uses.
  5. a)  NGL'S / LPG'S - field: Includes production derived from natural gas at the field processing plants. Report production measured after solvent flood or other ‘own-uses’.
    b) NGL'S / LPG'S - reprocessing plants: Includes production derived from natural gas at reprocessing/straddle plants. Report gross production before accounting for gas shrinkage of purchased gas or NGL'S at the extraction operations.
  6. a) Pentanes plus - fields: Includes production derived from natural gas at the field processing plants. Do not include field condensates recovered at the wellhead, which should be reported with conventional crude oil.
    b) Pentanes plus - reprocessing plants: Includes production derived from natural gas at reprocessing/straddle plants.
  7. Sulphur: Report here production measured in thousands of metric tonnes. Please report your total production whether it was sold or charged to inventory.

Schedule VI – Balance Sheet

  1. Total Current Assets: Includes such items as cash, marketable securities, accounts receivable, inventories, etc.
  2. Net Capital Assets: Includes land not held for the purpose of re-sale, amortizable assets such as buildings, machinery and equipment, etc.
  3. Other Assets: Include all assets not reported as either current or capital assets.
  4. Total Assets: Equals the sum of lines 1 to 3.
  5. Current Liabilities: Includes such items as current portion of long-term debt, accounts payable, notes payable, etc.
  6. Long Term Debt: Includes all debt with a maturity of greater than one year.
  7. Other Liabilities: Include all liabilities not reported as either a current liability or long-term debt
  8. Equity: Includes common shares, preferred shares, retained earnings and all other equity.
  9. Total Liabilities and Equity: The sum of lines 5 to 8.

Metric Conversion Factors

To convert from

Million cubic feet

  • (106cf) – gas

Million cubic metres

  • (106m3)

Divide by

  • 35.315

Thousand barrels

  • (103Bbls) - oil

Thousands cubic metres

  • (103m3)

Divide by

  • 6.29

Please note: Data are published annually in Catalogue 26-213, Oil and Gas Extraction.

Schedule VII – Non-Conventional Sector

The Non-Conventional Sector relates to operations as defined in the A.E.U.B. Publication Alberta Active Projects –Oil Sands and Heavy Oil Schemes (Catalogue A.E.U.B. ST-97-44). Effectively, these operations take place in the geographical areas of Cold Lake, Peace River, Athabasca, Wabasca and Lindbergh, etc.

Machinery and Equipment:

Include items such as boilers, compressors, motors, pumps and any other items that may be termed manufacturing or mining equipment as opposed to a fixed installation such as a building.

Capital Construction (Building and Engineering):

Construction structures should be classified to an asset according to its principle use unless it is a multi-purpose structure where we would like you to separate the components. The cost of any machinery and equipment which is an integral or built-in feature ( i.e. elevators, heating equipment, sprinkler systems, environmental controls, intercom system etc. ) should be reported as part of that structure as well as landscaping, associated parking lots, etc.

Agriculture Statistics Program Review

Consultation objectives

Statistics Canada sought feedback from users of agriculture statistics regarding their information needs and their opinions related to the agriculture statistics program at Statistics Canada.

This consultation informed the review of the agriculture statistics program, whose goal was to identify ways to reduce respondent burden and cost while maintaining the relevance and quality of the data produced.

Consultation method

The consultations were conducted between May 2011 and April 2012, using a variety of mechanisms, including workshops, face-to-face discussions, electronic surveys and telephone interviews.

Consultation participants included federal, provincial and municipal government officials, academics, producer organization and industry stakeholders.

How to get involved

This consultation is completed.

Individuals who wish to obtain more information or to take part in a consultation should contact Statistics Canada through the National Contact Centre.

Please note that Statistics Canada selects participants for each consultation to ensure feedback is sought from a representative sample of the target population for the study. Not all applicants will be asked to participate in a given consultation.

Results

Consultation results are posted online in the online report Agriculture Statistics Program Review.

Report a problem or mistake on this page
Date modified:

Concepts, definitions and data quality

The Monthly Survey of Manufacturing (MSM) publishes statistical series for manufacturers – sales of goods manufactured, inventories, unfilled orders and new orders. The values of these characteristics represent current monthly estimates of the more complete Annual Survey of Manufactures and Logging (ASML) data.

The MSM is a sample survey of approximately 10,500 Canadian manufacturing establishments, which are categorized into over 220 industries. Industries are classified according to the 2007 North American Industrial Classification System (NAICS). Seasonally adjusted series are available for the main aggregates.

An establishment comprises the smallest manufacturing unit capable of reporting the variables of interest. Data collected by the MSM provides a current ‘snapshot’ of sales of goods manufactured values by the Canadian manufacturing sector, enabling analysis of the state of the Canadian economy, as well as the health of specific industries in the short- to medium-term. The information is used by both private and public sectors including Statistics Canada, federal and provincial governments, business and trade entities, international and domestic non-governmental organizations, consultants, the business press and private citizens. The data are used for analyzing market share, trends, corporate benchmarking, policy analysis, program development, tax policy and trade policy.

1. Sales of goods manufactured

Sales of goods manufactured (formerly shipments of goods manufactured) are defined as the value of goods manufactured by establishments that have been shipped to a customer. Sales of goods manufactured exclude any wholesaling activity, and any revenues from the rental of equipment or the sale of electricity. Note that in practice, some respondents report financial trans­ac­tions rather than payments for work done. Sales of goods manufactured are available by 3-digit NAICS, for Canada and broken down by province.

For the aerospace product and parts, and shipbuilding industries, the value of production is used instead of sales of goods manufactured. This value is calculated by adjusting monthly sales of goods manufactured by the monthly change in inventories of goods / work in process and finished goods manufactured. Inventories of raw materials and components are not included in the calculation since production tries to measure "work done" during the month. This is done in order to reduce distortions caused by the sales of goods manufactured of high value items as completed sales.

2. Inventories

Measurement of component values of inventory is important for economic studies as well as for derivation of production values. Respondents are asked to report their book values (at cost) of raw materials and components, any goods / work in process, and fin­ished goods manufactured inventories separately. In some cases, respondents estimate a total inventory figure, which is allocated on the basis of proportions reported on the ASML. Inventory levels are calculated on a Canada‑wide basis, not by province.

3. Orders

a) Unfilled Orders

Unfilled orders represent a backlog or stock of orders that will generate future sales of goods manufactured assuming that they are not cancelled. As with inventories, unfilled orders and new orders levels are calculated on a Canada‑wide basis, not by province.

The MSM produces estimates for unfilled orders for all industries except for those industries where orders are customarily filled from stocks on hand and order books are not gen­erally maintained. In the case of the aircraft companies, options to purchase are not treated as orders until they are entered into the account­ing system.

b) New Orders

New orders represent current demand for manufactured products. Estimates of new orders are derived from sales of goods manufactured and unfilled orders data. All sales of goods manufactured within a month result from either an order received during the month or at some earlier time. New orders can be calculated as the sum of sales of goods manufactured adjusted for the monthly change in unfilled orders.

4. Non-Durable / Durable goods

a) Non-durable goods industries include:

Food (NAICS 311),
Beverage and Tobacco Products (312),
Textile Mills (313),
Textile Product Mills (314),
Clothing (315),
Leather and Allied Products (316),
Paper (322),
Printing and Related Support Activities (323),
Petroleum and Coal Products (324),
Chemicals (325) and
Plastic and Rubber Products (326).

b) Durable goods industries include:

Wood Products (NAICS 321),
Non-Metallic Mineral Products (327),
Primary Metals (331),
Fabricated Metal Products (332),
Machinery (333),
Computer and Electronic Products (334),
Electrical Equipment, Appliance and Components (335),
Transportation Equipment (336),
Furniture and Related Products (337) and
Miscellaneous Manufacturing (339). 

Survey design and methodology

Beginning with the August 1999 reference month, the Monthly Survey of Manufacturing (MSM) underwent an extensive redesign.

Concept Review

In 1998, it was decided that before any redesign work could begin the basic concepts and definitions of the program would be confirmed.

This was done in two ways: First, a review of user requirements was initiated. This involved revisiting an internal report to ensure that the user requirements from that exercise were being satisfied. As well, another round of internal review with the major users in the National Accounts was undertaken. This was to specifically focus on any data gaps that could be identified.

Secondly, with these gaps or 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.

In 2007, the MSM terminology was updated to be Charter of Accounts (COA) compliant. With the August 2007 reference month release the MSM has harmonized its concepts to the ASML. The variable formerly called “Shipments” is now called “Sales of goods manufactured”. As well, minor modifications were made to the inventory component names. The definitions have not been modified nor has the information collected from the survey.

Methodology

The latest sample design incorporates the 2007 North American Industrial Classification Standard (NAICS). Stratification is done by province with equal quality requirements for each province. Large size units are selected with certainty and small units are selected with a probability based on the desired quality of the estimate within a cell.

The estimation system generates estimates using the NAICS. The estimates will also continue to be reconciled to the ASML. Provincial estimates for all variables will be produced. A measure of quality (CV) will also be produced.

Components of the Survey Design

Target Population and Sampling Frame

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 Sample

The MSM sample is a probability sample comprised of approximately 10,500 establishments. A new sample was chosen in the autumn of 2006, followed by a six-month parallel run (from reference month September 2006 to reference month February 2007). The refreshed sample officially became the new sample of the MSM effective in January 2007.

This marks the first process of refreshing the MSM sample since 2002. 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.

Data Collection

Only a subset of the sample establishments is sent out for data collection. For the remaining units, information from administrative data files is used as a source for deriving sales of goods manufactured data. For those establishments that are surveyed, data collection, data capture, preliminary edit and follow-up of non-respondents are all performed in Statistics Canada regional offices. Sampled establishments are contacted by mail or telephone according to the preference of the respondent. Data capture and preliminary editing are performed simultaneously to ensure the validity of the data.

In some cases, combined reports are received from enterprises or companies with more than one establishment in the sample where respondents prefer not to provide individual establishment reports. Businesses, which do not report or whose reports 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, Statistics Canada has been investigating various alternatives to survey taking. Administrative data files are a rich source of information for business data and Statistics Canada is working at mining this rich data source to its full potential. As such, effective the August 2004 reference month, the MSM reduced the number of simple establishments in the sample that are surveyed directly and instead, 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.

In conjunction with the most recent sample, effective January 2007, approximately 2,500 simple establishments were selected to represent the GST portion of the sample.

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. With the most recent sample, the eligibility rules for GST-based establishments were refined to have more GST-based establishments in industries that typically carry fewer inventories. This way the impact of the GST-based establishments which require the estimation of inventories, will be kept to a minimum.

Detailed information on the methodology used for modelling sales of goods manufactured from administrative data sources can be found in the ‘Monthly Survey of Manufacturing: Use of Administrative Data’ (Catalogue no. 31-533-XIE) document.

Data quality

Statistical Edit and Imputation

Data are analyzed within each industry-province cell. Extreme values are listed for inspection by the magnitude of the deviation from average behavior. Respondents are contacted to verify extreme values. Records that fail statistical edits are considered outliers and are not used for imputation.

Values are imputed for the non-responses, for establishments that do not report or only partially complete the survey form. A number of imputation methods are used depending on the variable requiring treatment. Methods include using industry-province cell trends, historical responses, or reference to the ASML. Following imputation, the MSM staff performs a final verification of the responses that have been imputed.

Revisions

In conjunction with preliminary estimates for the current month, estimates for the previous three months are revised to account for any late returns. Data are revised when late responses are received or if an incorrect response was recorded earlier.

Estimation

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.

Benchmarking

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 to 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. 

As of the January 2007 reference month, a new sample was introduced. 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.

Data confrontation and reconciliation

Each year, during the period when the Annual Survey of Manufactures and Logging section set their annual estimates, the MSM section works with the ASML section to confront and reconcile significant differences in values between the fiscal ASML and the annual MSM at the strata and industry level.

The purpose of this exercise of data reconciliation is to highlight and resolve significant differences between the two surveys and to assist in minimizing the differences in the micro-data between the MSM and the ASML.

Sampling and Non-sampling Errors

The statistics in this publication are estimates derived from a sample survey and, as such, can be subject to errors. The following material is provided to assist the reader in the interpretation of the estimates published.

Estimates derived from a sample survey are subject to a number of different kinds of errors. These errors can be broken down into two major types: sampling and non-sampling.

1. Sampling Errors

Sampling errors are an inherent risk of sample surveys. They result from the difference between the value of a variable if it is randomly sampled and its value if a census is taken (or the average of all possible random values). These errors are present because observations are made only on a sample and not on the entire population.

The sampling error depends on factors such as the size of the sample, variability in the population, sampling design and method of estimation. For example, for a given sample size, the sampling error will depend on the stratification procedure employed, allocation of the sample, choice of the sampling units and method of selection. (Further, even for the same sampling design, we can make different calculations to arrive at the most efficient estimation procedure.) The most important feature of probability sampling is that the sampling error can be measured from the sample itself.

2. Non-sampling Errors

Non-sampling errors result from a systematic flaw in the structure of the data-collection procedure or design of any or all variables examined. They create a difference between the value of a variable obtained by sampling or census methods and the variable’s true value. These errors are present whether a sample or a complete census of the population is taken. Non-sampling errors can be attributed to one or more of the following sources:

a) Coverage error: This error can result from incomplete listing and inadequate coverage of the population of interest.

b) Data response error: This error may be due to questionnaire design, the characteristics of a question, inability or unwillingness of the respondent to provide correct information, misinterpretation of the questions or definitional problems.

c) Non-response error: Some respondents may refuse to answer questions, some may be unable to respond, and others may be too late in responding. Data for the non-responding units can be imputed using the data from responding units or some earlier data on the non-responding units if available.

The extent of error due to imputation is usually unknown and is very much dependent on any characteristic differences between the respondent group and the non-respondent group in the survey. This error generally decreases with increases in the response rate and attempts are therefore made to obtain as high a response rate as possible.

d) Processing error: These errors may occur at various stages of processing such as coding, data entry, verification, editing, weighting, and tabulation, etc. Non-sampling errors are difficult to measure. More important, non-sampling errors require control at the level at which their presence does not impair the use and interpretation of the results.

Measures have been undertaken to minimize the non-sampling errors. For example, units have been defined in a most precise manner and the most up-to-date listings have been used. Questionnaires have been carefully designed to minimize different interpretations. As well, detailed acceptance testing has been carried out for the different stages of editing and processing and every possible effort has been made to reduce the non-response rate as well as the response burden.

Measures of Sampling and Non-sampling Errors

1. Sampling Error Measures

The sample used in this survey is one of a large number of all possible samples of the same size that could have been selected using the same sample design under the same general conditions. If it was possible that each one of these samples could be surveyed under essentially the same conditions, with an estimate calculated from each sample, it would be expected that the sample estimates would differ from each other.

The average estimate derived from all these possible sample estimates is termed the expected value. The expected value can also be expressed as the value that would be obtained if a census enumeration were taken under identical conditions of collection and processing. An estimate calculated from a sample survey is said to be precise if it is near the expected value.

Sample estimates may differ from this expected value of the estimates. However, since the estimate is based on a probability sample, the variability of the sample estimate with respect to its expected value can be measured. The variance of an estimate is a measure of the precision of the sample estimate and is defined as the average, over all possible samples, of the squared difference of the estimate from its expected value.

The standard error is a measure of precision in absolute terms. The coefficient of variation (CV), defined as the standard error divided by the sample estimate, is a measure of precision in relative terms. For comparison purposes, one may more readily compare the sampling error of one estimate to the sampling error of another estimate by using the coefficient of variation.

In this publication, the coefficient of variation is used to measure the sampling error of the estimates. However, since the coefficient of variation published for this survey is calculated from the responses of individual units, it also measures some non-sampling error.

The formula used to calculate the published coefficients of variation (CV) in Table 1 is:

CV(X) = S(X)/X

where X denotes the estimate and S(X) denotes the standard error of X.

In this publication, the coefficient of variation is expressed as a percentage.

Confidence intervals can be constructed around the estimate using the estimate and the coefficient of variation. Thus, for our sample, it is possible to state with a given level of confidence that the expected value will fall within the confidence interval constructed around the estimate. For example, if an estimate of $12,000,000 has a coefficient of variation of 10%, the standard error will be $1,200,000 or the estimate multiplied by the coefficient of variation. It can then be stated with 68% confidence that the expected value will fall within the interval whose length equals the standard deviation about the estimate, i.e., between $10,800,000 and $13,200,000. Alternatively, it can be stated with 95% confidence that the expected value will fall within the interval whose length equals two standard deviations about the estimate, i.e., between $9,600,000 and $14,400,000.

Text table 1 contains the national level CVs, expressed as a percentage, for all manufacturing for the MSM characteristics. For CVs at other aggregate levels, contact the Dissemination and Frame Services Section at (613) 951-9497, toll free: 1-866-873-8789 or by e-mail at manufact@statcan.gc.ca.

Text table 1
National Level CVs by Characteristic
Month Sales of goods manufactured % Raw materials and components inventories % Goods / work in process inventories % Finished goods manufactured inventories % Unfilled Orders %
Feb-11 0.74 1.22 1.72 1.38 1.93
Mar-11 0.74 1.21 1.66 1.33 2.77
Apr-11 0.76 1.20 1.73 1.33 2.70
May-11 0.77 1.20 1.71 1.40 2.67
Jun-11 0.77 1.16 1.76 1.41 2.73
Jul-11 0.74 1.19 1.80 1.41 2.64
Aug-11 0.78 1.26 1.87 1.38 2.62
Sep-11 0.80 1.28 1.88 1.38 2.61
Oct-11 0.83 1.25 1.86 1.35 2.66
Nov-11 0.87 1.28 1.78 1.36 2.69
Dec-11 0.80 1.39 1.78 1.36 2.61
Jan-12 0.89 1.30 1.83 1.38 2.65
Feb-12 0.86 1.35 1.82 1.40 2.70

 

2. Non-sampling Error Measures

The exact population value is aimed at or desired by both a sample survey as well as a census. We say the estimate is accurate if it is near this value. Although this value is desired, we cannot assume that the exact value of every unit in the population or sample can be obtained and processed without error. Any difference between the expected value and the exact population value is termed the bias. Systematic biases in the data cannot be measured by the probability measures of sampling error as previously described. The accuracy of a survey estimate is determined by the joint effect of sampling and non-sampling errors.

Three sources of non-sampling error in the MSM are non-response error, imputation error and the error due to editing. To assist users in evaluating these errors, weighted rates that are related to these three types of error are given in Text table 2. The following is an example of what is meant by a weighted rate. A cell with a sample of 20 units in which five respond for a particular month would have a response rate of 25%. If these five reporting units represented $8 million out of a total estimate of $10 million, the weighted response rate would be 80%.

The definitions of the three weighted rates noted in Text table 2 follow. The weighted response rate is the proportion of a characteristic’s total estimate that is based upon reported data (excluding data that has been edited). The weighted imputation rate is the proportion of a characteristic’s total estimate that is based upon imputed data. The weighted editing rate is the proportion of a characteristic’s total estimate that is based upon data that was edited (edited data may have been originally reported or imputed).

Text table 2 contains the three types of weighted rates for each of the characteristics at the national level for all of manufacturing. In the table, the rates are expressed as percentages.

Text Table 2
National Weighted Rates by Source and Characteristic
Characteristics Survey Source Administrative Data Source
Response Imputation Editing Modeled Imputation Editing
% % % % % %
Sales of goods manufactured 83.31 4.33 5.70 5.95 0.51 0.20
Raw materials and components 73.68 7.51 9.25 0.00 9.04 0.52
Goods / work in process 58.31 9.19 25.08 0.00 7.27 0.15
Finished goods manufactured 77.71 7.35 5.64 0.00 8.14 1.17
Unfilled Orders 49.65 5.04 40.73 0.00 3.89 0.70

Joint Interpretation of Measures of Error

The measure of non-response error as well as the coefficient of variation must be considered jointly to have an overview of the quality of the estimates. The lower the coefficient of variation and the higher the weighted response rate, the better will be the published estimate.

Seasonal Adjustment

Economic time series contain the elements essential to the description, explanation and forecasting of the behavior of an economic phenomenon. They are statistical records of the evolution of economic processes through time. In using time series to observe economic activity, economists and statisticians have identified four characteristic behavioral components: the long-term movement or trend, the cycle, the seasonal variations and the irregular fluctuations. These movements are caused by various economic, climatic or institutional factors. The seasonal variations occur periodically on a more or less regular basis over the course of a year. These variations occur as a result of seasonal changes in weather, statutory holidays and other events that occur at fairly regular intervals and thus have a significant impact on the rate of economic activity.

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. This method minimizes the impact of seasonal variations on the series and essentially consists of adding one year of estimated raw data to the end of the original series before it is seasonally adjusted per se. The estimated data are derived from forecasts using ARIMA (Auto Regressive Integrated Moving Average) models of the Box-Jenkins type.

The X-12 program uses primarily a ratio-to-moving average method. It is used to smooth the modified series and obtain a preliminary estimate of the trend-cycle. It also calculates the ratios of the original series (fitted) to the estimates of the trend-cycle and estimates the seasonal factors from these ratios. The final seasonal factors are produced only after these operations have been repeated several times.

The technique that is used essentially consists of first correcting the initial series for all sorts of undesirable effects, such as the trading-day and the Easter holiday effects, by a module called regARIMA. These effects are then estimated using regression models with ARIMA errors. The series can also be extrapolated for at least one year by using the model. Subsequently, the raw series, pre-adjusted and extrapolated if applicable, is seasonally adjusted by the X-12 method.

The procedures to determine the seasonal factors necessary to calculate the final seasonally adjusted data are executed every month. This approach ensures that the estimated seasonal factors are derived from an unadjusted series that includes all the available information about the series, i.e. the current month's unadjusted data as well as the previous month's revised unadjusted data.

While seasonal adjustment permits a better understanding of the underlying trend-cycle of a series, the seasonally adjusted series still contains an irregular component. Slight month-to-month variations in the seasonally adjusted series may be simple irregular movements. To get a better idea of the underlying trend, users should examine several months of the seasonally adjusted series.

The aggregated Canada level series are now seasonally adjusted directly, meaning that the seasonally adjusted totals are obtained via X-12-ARIMA. Afterwards, these totals are used to reconcile the provincial total series which have been seasonally adjusted individually.

For other aggregated series, indirect seasonal adjustments are used. In other words, their seasonally adjusted totals are derived indirectly by the summation of the individually seasonally adjusted kinds of business.

Trend

A seasonally adjusted series may contain the effects of irregular influences and special circumstances and these can mask the trend. The short term trend shows the underlying direction in seasonally adjusted series by averaging across months, thus smoothing out the effects of irregular influences. The result is a more stable series. The trend for the last month may be, subject to significant revision as values in future months are included in the averaging process.

Real manufacturing sales of goods manufactured, inventories, and orders

Changes in the values of the data reported by the Monthly Survey of Manufacturing (MSM) may be attributable to changes in their prices or to the quantities measured, or both. To study the activity of the manufacturing sector, it is often desirable to separate out the variations due to price changes from those of the quantities produced. This adjustment is known as deflation.

Deflation consists in dividing the values at current prices obtained from the survey by suitable price indexes in order to obtain estimates evaluated at the prices of a previous period, currently the year 2002. The resulting deflated values are said to be “at 2002 prices”. Note that the expression “at current prices” refer to the time the activity took place, not to the present time, nor to the time of compilation.

The deflated MSM estimates reflect the prices that prevailed in 2002. This is called the base year. The year 2002 was chosen as base year since it corresponds to that of the price indexes used in the deflation of the MSM estimates. Using the prices of a base year to measure current activity provides a representative measurement of the current volume of activity with respect to that base year. Current movements in the volume are appropriately reflected in the constant price measures only if the current relative importance of the industries is not very different from that in the base year.

The deflation of the MSM estimates is performed at a very fine industry detail, equivalent to the 6-digit industry classes of the North American Industry Classification System (NAICS). For each industry at this level of detail, the price indexes used are composite indexes which describe the price movements for the various groups of goods produced by that industry.

With very few exceptions the price indexes are weighted averages of the Industrial Product Price Indexes (IPPI). The weights are derived from the annual Canadian Input-Output tables and change from year to year. Since the Input-Output tables only become available with a delay of about two and a half years, the weights used for the most current years are based on the last available Input-Output tables.

The same price index is used to deflate sales of goods manufactured, new orders and unfilled orders of an industry. The weights used in the compilation of this price index are derived from the output tables, evaluated at producer’s prices. Producer prices reflect the prices of the goods at the gate of the manufacturing establishment and exclude such items as transportation charges, taxes on products, etc. The resulting price index for each industry thus reflects the output of the establishments in that industry.

The price indexes used for deflating the goods / work in process and the finished goods manufactured inventories of an industry are moving averages of the price index used for sales of goods manufactured. For goods / work in process inventories, the number of terms in the moving average corresponds to the duration of the production process. The duration is calculated as the average over the previous 48 months of the ratio of end of month goods / work in process inventories to the output of the industry, which is equal to sales of goods manufactured plus the changes in both goods / work in process and finished goods manufactured inventories.

For finished goods manufactured inventories, the number of terms in the moving average reflects the length of time a finished product remains in stock. This number, known as the inventory turnover period, is calculated as the average over the previous 48 months of the ratio of end-of-month finished goods manufactured inventory to sales of goods manufactured.

To deflate raw materials and components inventories, price indexes for raw materials consumption are obtained as weighted averages of the IPPIs. The weights used are derived from the input tables evaluated at purchaser’s prices, i.e. these prices include such elements as wholesaling margins, transportation charges, and taxes on products, etc. The resulting price index thus reflects the cost structure in raw materials and components for each industry.

The raw materials and components inventories are then deflated using a moving average of the price index for raw materials consumption. The number of terms in the moving average corresponds to the rate of consumption of raw materials. This rate is calculated as the average over the previous four years of the ratio of end-of-year raw materials and components inventories to the intermediate inputs of the industry.

Public consultation and notices - Geographic classifications

General notice

Standard Geographical Classification (SGC)

SGC 2006

Supplement no. 3

July 14, 2010 (Previous notice)

Supplement no. 3 to the Standard Geographical Classification 2006 is issued by Standards Division to inform users of a change of name of the census metropolitan area (CMA) of Kitchener.

Effective July 14, 2010, the name of the CMA of "Kitchener" becomes "Kitchener–Cambridge–Waterloo".

Divisions in Statistics Canada releasing data for that CMA are expected to use the new name at the earliest opportunity.

Data dissemination guidelines

Effective July 14, 2010, "Kitchener–Cambridge–Waterloo" is the official name of the CMA of Kitchener in the Standard Geographical Classification (SGC) 2006.

The following applies to data released in print, through CANSIM or electronically.

For non-Census products and programs, the new CMA name should be implemented at the earliest opportunity in any new release, regardless of the reference period of the data.

For the 2006 Census products, the former name will be maintained but a footnote should be added in any new release in The Daily text, or in any analytical text indicating the name change.

Supplement no. 2

May 25, 2009 (Previous notice)

Supplement no. 2 to the Standard Geographical Classification 2006 is issued by Standards Division to inform users of: (1) the guidelines for requesting a name change to a census metropolitan area; and (2) a change of name of the census metropolitan area (CMA) of Abbotsford.

1. Guidelines for Census Metropolitan Area (CMA) name change requests

The Census Metropolitan Area (CMA) Naming Convention has been revised for use in the 2011 Census and in other Statistics Canada products. Below are the guidelines for requesting a change:

CMA names can consist of up to three legislated municipal names of eligible Census subdivisions (CSDs) that are components of the CMA . However, the number of name elements in any new CMA name request is limited to five. If any of the eligible CSD names are already hyphenated or compound, the number of CSD names will be limited to two or one if the number of name elements exceeds five.

The eligible municipal names include the historic central municipality name and the two component CSD s with the largest population, and having a population of at least 10,000, according to the last census.

The ordering of the municipal names within the CMA name is determined by the historic (central) municipality and the population size of the eligible CSD s. The first component of the CMA name is always the historic (central) CSD even if its census population count is less than the other eligible component CSD s. This ensures that CMA names retain a measure of stability for better longitudinal recognition. The second and third place name order is determined by population size. The component CSD with the higher census population count at the time of the name change assumes the second position and the next largest component CSD the third position.

In order for Statistics Canada to implement a requested CMA name change, there must be explicit consensus among all eligible component municipalities on a proposed new name and a formal request, in accordance with these Guidelines, must be sent to the Director of the Geography Division at Statistics Canada by June 1st of the year prior to the Census. The CMA name change will be implemented in the revision of the Standard Geographical Classification related to the Census under consideration.

Statistics Canada will continue to change CMA names whenever the legislated name of a municipality changes. Any other request for a name change will only be considered within the context of these guidelines.

This naming convention and these guidelines will be included under Information on the Standard Geographical Classification in the Naming geographical units section of the classification manual.

2. Change of name – Census Metropolitan Area of Abbotsford

Effective May 25, 2009, the name of the CMA of “Abbotsford” becomes “Abbotsford–Mission”.

Divisions in Statistics Canada releasing data for that CMA are expected to use the new name at the earliest opportunity.

Data dissemination guidelines

Effective May 25, 2009, “Abbotsford–Mission” is the official name of the CMA of Abbotsford in the Standard Geographical Classification (SGC) 2006.

The following applies to data released in print, through CANSIM or electronically.

For non-Census products and programs, the new CMA name should be implemented at the earliest opportunity in any new release, regardless of the reference period of the data.

For the 2006 Census products, the former name will be maintained but a footnote should be added in any new release in The Daily text, or in any analytical text indicating the name change.

April 08, 2009 (Previous notice)

The Census Metropolitan Area (CMA) Naming Convention is currently being revised for use in the 2011 Census. The key revision to the convention is the addition of Guidelines for Name Change Requests for municipalities.

At this time, Statistics Canada is soliciting comments from users on the proposed New (CMA) Naming Convention and Guidelines for (CMA) Name Change Requests.

The naming convention and guidelines may be viewed at:

Proposed New Census Metropolitan Area (CMA) Naming Convention and Guidelines for (CMA) Name Change Requests.

Comments should be sent to standards@statcan.gc.ca.

The deadline for comments is April 30th, 2009.

December 12, 2008 (Previous notice)

A census metropolitan area (CMA) is formed by one or more adjacent municipalities centred on a large urban area. To be included in the CMA municipalities must have a high degree of integration with the central urban area, as measured by commuting flows derived from census place of work data.

The current convention for the naming of a CMA is based on the name of the principal urban area or largest city at the time the CMA was first formed. This standard has been used since the 1971 Census. Through the years, the CMA names have remained relatively stable. The most important changes resulted from name changes to the census subdivisions (resulting from municipal dissolutions, incorporations and name changes).

In recent years, Statistics Canada has received a number of requests to change the CMA naming convention to include additional component municipality names in the name of the CMA . In response to these requests, Statistics Canada is considering a new naming convention.

The existing CMA names will be maintained for the next Census unless a formal request for a name change is received according to the following guidelines.

Guidelines for Census Metropolitan Area name change requests

  1. CMA names can consist of up to three legislated municipal names of eligible Census subdivisions (CSDs) that are components of the CMA . However, the number of name elements in any new CMA name request is limited to five. If any of the eligible CSD names are already hyphenated or compound, the number of CSD names will be limited to two or one if the number of name elements exceeds five.
  2. The eligible municipal names include the historic central municipality name and the two component CSD s with the largest population, and having a population of at least 10,000, according to the last census.
  3. The ordering of the municipal names within the CMA name is determined by the historic (central) municipality and the population size of the eligible CSD s. The first component of the CMA name is always the historic (central) CSD even if its census population count is less than the other eligible component CSD s. This ensures that CMA names retain a measure of stability for better longitudinal recognition. The second and third place name order is determined by population size. The component CSD with the higher census population count at the time of the name change assumes the second position and the next largest component CSD the third position.
  4. In order for Statistics Canada to implement a requested CMA name change there must be explicit consensus among all eligible component municipalities on a proposed new name and a formal request, in accordance with these Guidelines, must be sent to the Director of the Geography Division at Statistics Canada by June 1st of the year prior to the Census.
  5. Statistics Canada will change CMA names whenever the legislated name of a municipality changes. Any other request for a name change will only be considered within the context of these guidelines.

For definitions and an overview of the current CMA and CA methodology applied for the 2006 Census, see 2006 Census Dictionary:

Archived Census metropolitan area (CMA) and census agglomeration (CA) Archived

Supplement no. 1

October 20, 2008

Supplement no. 1 to the Standard Geographical Classification 2006 is issued by Standards Division to inform users of the official names in English and French for the territory of the Yukon.

Effective October 20, 2008, the names "Yukon Territory" in English and "Territoire du Yukon" in French become "Yukon" in English and in French, as per the Yukon Act (Chapter 7, assented March 27, 2002).

Divisions in Statistics Canada releasing data for that territory are expected to use the new name at the earliest opportunity.

Official abbreviations

Users should be aware that there is no change to the abbreviations as well as to the numeric and alpha codes for Yukon. The abbreviations remain Y.T. in English and Yn in French, and 60 for the numeric code and YT for the alpha code.

For a complete list see abbreviations.

Divisions, when using provincial/territorial abbreviations for releasing data, are expected to implement these abbreviations.

Data dissemination guidelines

Effective October 20, 2008, "Yukon" is the official name, in both English and French, of the territory of the Yukon in the Standard Geographical Classification (SGC) 2006.

The following applies to data released in print, through CANSIM or electronically.

For non-Census products and programs, the new territory name and its abbreviations should be implemented at the earliest opportunity in any new release, regardless of the reference period of the data.

For the 2006 Census products, the former name will be maintained but a footnote should be added in any new release in the Daily text, or in any analytical text indicating the name change.

November 10, 2007

The Classification of Instructional Programs (CIP) is currently being revised. The revised CIP will be introduced for Census 2011.

At this time, Statistics Canada is soliciting input from data producers and data users to ensure their needs continue to be met by the CIP . Proposals for changes to the CIP for 2011 should be submitted to standards-normes@statcan.gc.ca. A CIP Revision Consultation Guide has been produced to help you provide input.

Input is requested by January 15, 2008 but will be accepted until September 15, 2008. Decisions on proposed revisions will be made throughout 2008. To enable us to fully consider your suggestions in time for inclusion in this revision, please send them early in the consultation period. You may send more than one submission, if that enables you to comment earlier.

Consultation Guide

Please consider the following questions when preparing your input to the consultation on the revision of the Classification of Instructional Programs (CIP). Submissions do not need to cover all the topics. Comments can be submitted on your particular area(s) of concern only.

Note: The CIP may be viewed at:

Archived Classification of Instructional Programs (CIP) Canada 2000 Archived

Questions related to specific programs (categories in CIP that have a 6-digit code)

Are there programs for which you cannot find a satisfactory code? For each program you list, please identify one or more institutions where it is offered.

Are there programs currently being coded to a .9999 category that you would prefer to see in a more specific category? Why? (Perhaps you feel there are adequate numbers to justify identifying it specifically. Perhaps it is of some analytical significance.) For each program you list, please identify one or more institutions where it is offered.

Are there categories you find difficult to use because the descriptions are vague or unclear?

Are there pairs of categories you find difficult to distinguish from each other? Are there boundaries that could be clarified?

We would also like to understand better how the 6-digit level of the CIP is used.

  • Please summarize briefly how you or others in your institution/department use the CIP 6-digit level.
  • Are 6-digit CIP codes used in any administrative processes?
  • Is any comparison made between Canadian data and CIP -based data from the United States?

Questions related to higher levels of aggregation in the CIP

The specific program codes in the CIP are organized in subseries that are identified with 4-digit codes ( e.g. , 16.17).

  • Do you use codes at this level of aggregation?
  • If so, how do you use them? For what purpose?
  • Are there changes you would like to see in any of the groups at this level of aggregation? Please be as specific as possible in your comments, identifying the changes you would like to see and why.

Subseries are organized in series that are identified with 2-digit codes ( e.g. , 16).

  • Do you use codes at this level of aggregation?
  • If so, how do you use them? For what purpose?
  • Are there changes you would like to see in any of the groups at this level of aggregation? Please be as specific as possible in your comments, identifying the changes you would like to see and why.

Questions related to the use of CIP to code courses

Though designed as a classification of programs of study, the CIP has also been used to code specific courses. For example, it has been used to code courses taken by adults as part of their lifelong learning. Statistics Canada would like to understand better the analytic uses of data about courses so that we may consider the best way to address these specific needs.

If you use information on courses,

  • Are the learners adults?
  • What is your objective or analytical purpose when using this information?
  • More specifically,
    • What do you want to know about the content of the course? For example, do you want to know the specific subject (such as, leadership, management, computer-related, safety training, CPR, literacy) or something more general ( e.g. , generic skill development or specific professional development). What categories would help you explore the questions or issues that concern you?
    • Some courses relate to specific occupations whose training programs are coded in CIP . For example, the Smart Serve course is for bartenders. Would you like to see such courses coded with training for that occupation? ( i.e. , Smart Serve would be coded to CIP 12.0502 along with bartender training programs.) If people preparing to enter an occupation were coded to the same group as people already in the occupation who are engaging in professional development, would that support or hinder your analyses?
    • Some courses have the same name as an academic program in CIP , such as computer technology. When adults report such courses, they could be taking a single course; they could be enrolled in the program; or, they could be enrolled in another program toward which that course credit could be applied. Would you like to see such courses coded to the closest CIP code? If not, what categories would enable you to do the type of analysis you want to do?
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