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 Marketing and Dissemination Section at (613) 951-9497, toll free: 1-866-873-8789 or by e-mail at manufact@statcan.gc.ca.

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.

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.

Agriculture Division

Confidential when completed

This survey is conducted under the authority of the Statistics Act, Revised Statutes of Canada, 1985, c. S-19. Completion of this questionnaire is a legal requirement under the Statistics Act.

Province:

For the Fur Year:

The purpose of this survey is to produce annual estimates of the quantity and value of wildlife pelts produced in Canada. The information is used by all levels of governments in developing policies and in addressing issues such as dealing with conservation of wildlife.

Newfoundland and Labrador, New Brunswick, Manitoba, Saskatchewan, and British Columbia residents please note: To avoid duplication of enquiry, this survey is conducted under a co-operative agreement for the sharing of information in accordance with:

Section 12, Statistics Act with the Newfoundland and Labrador, New Brunswick, Manitoba, Saskatchewan, and British Columbia Departments of Agriculture.

If you object to sharing this information, please inform us in writing and mail your letter, along with the completed questionnaire, to Agriculture Division, Statistics Canada, Ottawa Ontario, K1A 0T6.

Quebec only: A data sharing arrangement exists under Section 11 of the Statistics Act with the Quebec Bureau of Statistics.

Kind
Wildlife Pelts

• Number of Pelts #
• Average Value Received $
• Total Value received

a. Badger
b. Bear:

• Black or brown
• Grizzly
• White (polar)

c. Beaver
d. Bobcat
e. Coyote
f.  Ermine (weasel)
g. Fisher
h. Fox:

• Blue
• Cross
• Red
• Silver or black
• White (arctic)
• Other (please specify)

i. Lynx
j. Marten
k. Mink (wild)
l. Muskrat
m. Otter
n. Rabbit
o. Raccoon
p. Seal (hair)
q. Skunk
r. Squirrel
s. Wolf
t. Wolverine
u. Other (please specify)
Total

Name
Date
Address

*Note: The prices should be those paid to trappers (excluding royalty payments, etc.). Adherence to this allows proper comparisons of the data from each provincial and territorial government.

Agriculture Division

Confidential (when completed)

This survey is conducted under the authority of the Statistics Act, Revised Statutes of Canada, 1985, c. S-19. Completion of this questionnaire is a legal requirement under the Statistics Act.

Si vous préférez ce questionnaire en français, veuillez cocher.

The purpose of this survey is to produce annual estimates of fur farm pelts produced in Canada. The information is used by all levels of government in developing policies and in addressing issues related to the fur industry.

Newfoundland and Labrador, New Brunswick, Manitoba, Saskatchewan and British Columbia residents please note: To avoid duplication of enquiry this survey is conducted under a cooperative agreement for the sharing of information in accordance with:

Section 12, Statistics Act with the Newfoundland and Labrador, New Brunswick, Manitoba, Saskatchewan and British Columbia Departments of Agriculture.

If you object to sharing this information please inform us in writing and mail your letter, along with the completed questionnaire to the Agriculture Division, Statistics Canada, Ottawa, Ontario, K1A 0T6.

Quebec Only: A data sharing arrangement exists under Section 11 of the Statistics Act with the L'Institut de la statistique du Québec.

Instructions
Read each question carefully. When a question does not apply, put in a "0".
Where a mink/fox has died BUT was pelted, report it in the question on peltings.
INCLUDE mink/fox boarded by you for others in answering questions in this report.
EXCLUDE mink/fox boarded for you by others.

Please correct name or address if necessary.

Farm Name (if applicable)
Surname or Family Name
Usual First Name and Initital
Area Code
Telephone
R.R.
Box No.
Number and Street Name
Postal Code
Post Office (name of city, town or village where mail is received)
Partner's Name (if applicable)
Telephone
Partner's Name (if applicable)
Telephone
Corporation Name (if different from farm name)
Headquarters

Mink/Foxes Boarded for Others at December 31, 2009
Name of Owner:
Address:
Name of Owner:
Address:

Live Mink/Foxes Sold during 2009
Name of Purchaser:
Address:
Name of Purchaser:
Address:

Live Mink/Foxes Purchased during 2009
Name of Seller:
Address:
Name of Seller:
Address:

Section A:

Mink (#)
Fox (#)

1. Live on farm at January 1, 2009
(a) male
(b) female
2. Bought in 2009
3. Taken as boarders in 2009
4. Kits (pups) born in 2009
5. Total (sum of 1 to 4)
Must equal total on line 12
6. Sold live in 2009
7. Boarders removed alive in 2009
8. Peltings in 2009 (include pelts taken from animals that died and spring peltings)
9. Died (not pelted); include loss of kits (pups)
10. Escaped or lost
11. Live on farm at December 31, 2009
(a) male
(b) female
12. Total (sum of 6 to 11)
Must equal total on line 5

Section B: Mink Pelts

Number

1. Dark
2. Demi-buff
3. Pastel (including buff, dawn, orchid)

4. Sapphire
5. Pearl
6. Aleutian (including iris)
7. Violet
8. White
9. Silver Blue
10. Lavender
11. Blush
12. Mahogany
13. Other
14. Total Mink Pelted in 2009 (sum of lines 1 to 13)
Must equal code 928 in Section A

Section C: Fox Pelts

Number

1. Silver
2. Pearl
3. Platinum
4. Glacier
5. Ranched Red
6. Ranched Cross
7. Blue
8. Amber
9. Other
10. Total Foxes Pelted in 2009 (sum of lines 1 to 9)
Must equal code 828 in Section A

Comments

1. Family income and related variables: Sub-provincial data
2. Migration Estimates

• Abbotsford (Abbotsford–Mission since May 2009)
• Barrie
• Brantford
• Calgary
• Edmonton
• Greater Sudbury
• Guelph
• Halifax
• Hamilton
• Kelowna
• Kingston
• Kitchener (Kitchener–Cambridge–Waterloo since July 2010)
• London
• Moncton
• Montréal
• Oshawa
• Ottawa–Gatineau, Ontario part
• Ottawa–Gatineau, Quebec part
• Peterborough
• Québec
• Regina
• Saguenay
• Saint John
• Saskatoon
• Sherbrooke
• St. Catharines–Niagara
• St. John's
• Thunder Bay
• Toronto
• Trois-Rivières
• Vancouver
• Victoria
• Windsor
• Winnipeg

New Housing Price Indexes

• Calgary — Census Metropolitan Area
• Charlottetown — Census Agglomeration
• Edmonton — Census Metropolitan Area
• Fredericton — Census Agglomeration
• Greater Sudbury — Census Metropolitan Area
• Halifax — Census Metropolitan Area
• Hamilton — Census Metropolitan Area
• Kitchener (Kitchener–Cambridge–Waterloo since July 2010) — Census Metropolitan Area
• London — Census Metropolitan Area
• Moncton — Census Metropolitan Area
• Montréal — Census Metropolitan Area
• Oshawa — Census Metropolitan Area
• Ottawa–Gatineau, Ontario part — Census Metropolitan Area
• Ottawa–Gatineau, Quebec part — Census Metropolitan Area
• Québec — Census Metropolitan Area
• Regina — Census Metropolitan Area
• Saint John — Census Metropolitan Area
• Saskatoon — Census Metropolitan Area
• St. Catharines–Niagara — Census Metropolitan Area
• St. John's — Census Metropolitan Area
• Thunder Bay — Census Metropolitan Area
• Toronto — Census Metropolitan Area
• Vancouver — Census Metropolitan Area
• Victoria — Census Metropolitan Area
• Windsor — Census Metropolitan Area
• Winnipeg — Census Metropolitan Area

Value of building permits

Investment in non-residential building construction

• Abbotsford (Abbotsford–Mission since May 2009)
• Barrie
• Brantford
• Calgary
• Edmonton
• Greater Sudbury
• Guelph
• Halifax
• Hamilton
• Kelowna
• Kingston
• Kitchener (Kitchener–Cambridge–Waterloo since July 2010)
• London
• Moncton
• Montréal
• Oshawa
• Ottawa–Gatineau, Ontario part
• Ottawa–Gatineau, Quebec part
• Peterborough
• Québec
• Regina
• Saguenay
• Saint John
• Saskatoon
• Sherbrooke
• St. Catharines–Niagara
• St. John's
• Thunder Bay
• Toronto
• Trois-Rivières
• Vancouver
• Victoria
• Windsor
• Winnipeg

Purpose

To familiarize participants with basic and intermediate techniques for the statistical analysis of data. It is a theoretical course with exercises (with/without SAS), and hence is not a data analysis course.

Benefits to participants

The participants will be better able to determine the type of analytical work to undertake and to read research papers. They will also acquire familiarity with SAS results.

Target population

Employees with basic knowledge of mathematics and statistics who are called upon to solve problems of data exploration and analysis.

Course outline

• Standard probability distributions and tables
• Point estimation
• Confidence intervals
• Tests of hypothesis
• Simple linear regression
• *Analysis of residuals
• Presentation of SAS.

   * time permitting

Prerequisites

Basic knowledge of mathematics and statistics.

Duration: 4 days

Center for Education Statistics
Statistics Canada

General description

This manual describes the data elements to be included in the Registered Apprenticeship Information System (RAIS). The survey was designed to replace the Registered Apprenticeship Training Survey for the 1991 reporting year.

The data reported should consist of one record for every individual registered in the apprenticeship system during the reporting year. All data elements should be reported for registered apprentices. The required information for trade qualifiers (challengers) include several of the data elements, however, the ones not requested include data elements 28, 33 to 36 and 39 to 57.

For each data element, which is identified by name and element number, there is a complete description of the data required for the element, definitions of terms where appropriate and a complete listing of all of the possible codes that can be used. In addition, some specific examples are included where additional clarification is required to ensure consistent interpretation of the elements.

A total of 19 data elements have been identified as mandatory elements. These are considered as being the core information needed on registered apprenticeship programs and trade qualifiers in order to enable Statistics Canada to release annual statistics on registrations, completions and certifications. These mandatory elements are the following: data elements 1 to 3, 5, 20, 21, 29 to 36, 38, 39, 41, 58 and 59.

To facilitate the processing of the input data into the RAIS system, it is best that the reported data file be sent in a flat file format with a ".txt" extension. The data file should also not contain delimiters of any sort and have a record length of 752 bytes.

In addition to the data report, it would be appreciated if a separate file with the most recent list of trade codes and their description can also be made available.

Elements reserved for Statistics Canada

A total of nine elements are reserved for Statistics Canada; these are either elements that Statistics Canada will be deriving or elements that are meant to be used internally only.

Jurisdictions are not to report information for these elements. A list of these seven elements is available in the last section of this document (p. 66).

Element No. 1: Reporting year

Description
The calendar year for which the reported data is valid and should consist of a complete calendar year from January 1 to December 31.

Report for the apprentice or trade qualifier (challenger).

Size of Field: 4 digits numeric

Codes
YYYY (Year)

Element No. 2: Jurisdiction

Description
Using the Statistics Canada province and territory codes, identify the jurisdiction submitting the data.

Report for the apprentice or trade qualifier (challenger).

Size of Field: 2 digits numeric.

Codes
10 – Newfoundland
11 – Prince Edward Island
12 – Nova Scotia
13 – New Brunswick
24 – Quebec
35 – Ontario
46 – Manitoba
47 – Saskatchewan
48 – Alberta
59 – British Columbia
60 – Yukon
61 – Northwest Territories
62 – Nunavut
99 – Unknown

Element No. 3: Identification number

Description
A unique identifier for each individual record and representing either an apprentice or trade qualifier (challenger). It should remain consistent from reporting year to reporting year.

Consistent reporting of the same unique identifier should be maintained for the same individual, across reporting periods. However, if a change should occur in your unique identifier, ensure Statistics Canada is informed of this change, and include concordance information in your next reporting to bridge this change.

In this element, report a unique identifier, (not the Social Insurance Number, S.I.N.) used by your jurisdiction, such as a registered apprenticeship registration number, client number, etc.

If the S.I.N. is also available, report using the next data element no. 4 - Social Insurance Number.

Size of Field: Maximum of 12 characters

Codes
Can be a combined character and numeric field.

Element No. 4: Social Insurance Number (SIN)

Description
The Social Insurance Number (SIN) of the apprentice or trade qualifier (challenger).

Size of Field: 9 digits numeric

Codes
9-digit SIN

Element No. 5: Apprentice or trade qualifier indicator

Description
In this element indicate if the individual is a registered apprentice or a trade qualifier (challenger).

Size of Field: 1 digit numeric

Codes
1 – Registered apprentice
2 – Trade qualifier (challenger)
9 – Unknown

Element No. 6: First name

Description
First name of the apprentice or trade qualifier (challenger).

Apprentice's or trade qualifier (challenger)'s first (given) name.

Size of Field: Maximum of 25 characters

Codes
N/A

Element No. 7: Middle name

Description
Middle name of the apprentice or trade qualifier (challenger).

Note: If you cannot report the first name and middle name as separate fields, enter both names in the previous element no. 6 - First name, and leave this element blank.

Size of Field: Maximum of 25 characters

Codes
N/A

Element No. 8: Last/Family name

Description
Family or last name of the apprentice or trade qualifier (challenger).

Apprentice's or trade qualifier (challenger)'s surname (last name).

Size of Field: Maximum of 30 characters

Codes
N/A

Element No. 9: Address

Description
The address number, apartment number (if applicable), street name, PO Box or RR route (if applicable) of the current residence of the apprentice or trade qualifier (challenger).

Report as one string the address information of the current residence of the apprentice or trade qualifier (challenger). In addition to the address number, apartment number, street name and PO Box/RR route number, also include in this element the street type and direction of street (if applicable).

For street type, the short form abbreviation can be reported, such as St. for Street, Ave. for Avenue, etc.

The direction of the street can also be in the abbreviated form of N for North, S for South, etc. (N, S, E, W, NE, NW, SE, SW).

Other address information, such as city name, province/territory of residence and postal code should be reported as separate elements in no. 10 - City name, no. 11 - Jurisdiction of residence and no. 12 - Postal code.

Size of Field: Maximum of 125 characters

Codes
N/A

Element No. 10: City name

Description
Name of city or town of the current residence of the apprentice or trade qualifier (challenger).

Size of Field: Maximum of 60 characters

Codes
N/A

Element No. 11: Jurisdiction of residence

Description
This element identifies the province or territory of residence of the apprentice or trade qualifier (challenger).

Report using the Statistics Canada province and territory codes previously identified in the element no. 2 - Jurisdiction.
 
Size of Field: 2 digits numeric

Codes
10 – Newfoundland
11 – Prince Edward Island
12 – Nova Scotia
13 – New Brunswick
24 – Quebec
35 – Ontario
46 – Manitoba
47 – Saskatchewan
48 – Alberta
59 – British Columbia
60 – Yukon
61 – Northwest Territories
62 – Nunavut
99 – Unknown

Element No. 12: Postal code

Description
Postal code of the current residence of the apprentice or trade qualifier (challenger).

Size of Field: Maximum of 6 characters

Codes
Report as one complete string without space between the digits - (CNCNCN).

Element No. 13: Area code of work phone

Description
3-digit area code of the work phone number of the apprentice or trade qualifier (challenger).

Size of Field: 3 digits numeric

Codes
N/A

Element No. 14: Work phone number

Description
Work phone number of the apprentice or trade qualifier (challenger).

Size of Field: 7 digits numeric

Codes
N/A

Element No. 15: Work phone number extension

Description
Work phone number extension (if applicable) of the apprentice or trade qualifier (challenger).

Size of Field: 5 digits numeric

Codes
N/A

Element No. 16: Area code of home phone

Description
3-digit area code of the home phone number of the apprentice or trade qualifier (challenger).

Size of Field: 3 digits numeric

Codes
N/A

Element No. 17: Home phone number

Description
Home phone number of the apprentice or trade qualifier (challenger).

Size of Field: 7 digits numeric

Codes
N/A

Element No. 18: Area code of cell phone

Description
3-digit area code of the cell phone number of the apprentice or trade qualifier (challenger).

Size of Field: 3 digits numeric

Codes
N/A

Element No. 19: Cell phone number

Description
Cell phone number of the apprentice or trade qualifier (challenger).

Size of Field: 7 digits numeric

Codes
N/A

Element No. 20: Gender

Description
The gender of the apprentice or trade qualifier (challenger).

Size of Field: 1 digit numeric

Codes
1 – Male
2 – Female
9 – Unknown

Element No. 21: Date of birth

Description
Date of birth of the apprentice or trade qualifier (challenger).

Note: For this data element do not report any empty spaces, dashes or backslashes. Each field in this data element should be filled with a character (e.g. 03061985).

If not available, leave blank.

Size of Field: 8 digits numeric

Codes
DDMMYYYY (DayMonthYear)

Element No. 22: Aboriginal identity

Description
This element identifies the Aboriginal identity of the apprentice or trade qualifier (challenger), if applicable.

A person with Aboriginal identity includes someone who is a North American Indian/First Nations, a Métis or an Inuit. North American Indians/First Nations, which include Status Indians, as well as non-Status Indians.

A person with non-Aboriginal identity should be reported as code = 5.

Size of Field: 1 digit numeric

Codes
1 – North American Indian / First Nations
2 – Métis
3 – Inuit
4 – Person identifying with more than one group
5 – Person who does not self-identify with one of the groups (not an Aboriginal person)
9 – Unknown

Element No. 23: Disability or activity limitations

Description
This element identifies whether the apprentice or trade qualifier (challenger) has any disabilities or activity limitations because of physical or health problems.

Size of Field: 1 digit numeric

Codes
1 – Hearing impaired
2 – Vision impaired
3 – Wheel chair access
4 – Person with a disability or activity limitation not listed in the above
5 – Person with more than one disability or activity limitation
6 – Person with no reported disabilities or activity limitations
9 – Unknown

Element No. 24: Highest education level

Description
The highest achieved level of education obtained prior to registration in the current trade program.

If information on the highest level of education is not available, please report as code = 99.

Also report for trade qualifier (challenger), if information on the highest achieved level of education is available.

Size of Field: 2 digits numeric

Codes
01 – Completed some elementary school
02 – Completed elementary school
03 – Grade 7
04 – Grade 8
05 – Grade 9
06 – Grade 10
07 – Grade 11
08 – Grade 12
09 – Grade 13 (if applicable)
10 – High school graduation certificate or equivalency certificate
11 – Registered apprenticeship certificate
12 – Other trade certificate or diploma
13 – College, technical, CEGEP or non-university certificate or diploma (includes pre-employment/pre-apprenticeship program)
14 – College, technical, CEGEP or non-university certificate or diploma
15 – University
16 – Other
99 – Unknown

Element No. 25: Previous apprenticeship training

Description
This element identifies the trade in which the most recent previous apprenticeship training was obtained prior to the trade the apprentice is now currently registered.

The previous apprenticeship training can be in any trade, not necessarily similar to the one the apprentice is currently registered.

Note: If a certificate was obtained for the completion of previous apprenticeship training, report the information in element no. 60 – Prior trade certificate.

If applicable, also report for trade qualifier (challenger).

The identifier for this trade is the trade code used by the reporting jurisdiction.

Size of Field: Maximum of 10 characters

Codes
N/A

Element No. 26: Previous apprenticeship training date

Description
This element identifies the end date of any previous apprenticeship training if reported in element no. 25 - Previous apprenticeship training.

If applicable, also report for trade qualifier (challenger).

Note: For this data element do not report any empty spaces, dashes or backslashes. Each field in this data element should be filled with a character (e.g. 061985).

If not available, leave blank.

Size of Field: 6 digits numeric

Codes
MMYYYY (MonthYear)

Element No. 27: Previous apprenticeship training jurisdiction

Description
In this element, identify the province or territory in which the apprentice was registered and obtained previous apprenticeship training, if reported in element no. 25 - Previous apprenticeship training.

Report using the Statistics Canada province and territory codes previous identified in the element no. 2 - Jurisdiction. An additional code has been added to the province and territory codes to include previous training outside of Canada.

If applicable, also report for trade qualifier (challenger).

Size of Field: 2 digits numeric

Codes
10 – Newfoundland
11 – Prince Edward Island
12 – Nova Scotia
13 – New Brunswick
24 – Quebec
35 – Ontario
46 – Manitoba
47 – Saskatchewan
48 – Alberta
59 – British Columbia
60 – Yukon
61 – Northwest Territories
62 – Nunavut
98 – Outside Canada
99 – Unknown

Element No. 28: Business number (BN)

Description
In this element report the Business Number (BN) of the employer that is providing the current training to the registered apprentice.

The Business Number (BN) is a unique identification number given to each enterprise/business entity by the Canada Revenue Agency (CRA).

The standard size of the Business Number is of 15-characters. However, only the first 9-characters are required by Statistics Canada; these first 9-characters identify the business and always remain unchanged.

Therefore, only the first 9-characters of the Business Number (BN) are to be reported in this element.

Size of Field: Maximum of 9 characters

Codes
N/A

Element No. 29: Trade code

Description
The trade in which the apprentice is registered or trade qualifier (challenger) is certified.

The identifier for this trade is the trade code used by the jurisdiction.

If the trade code includes additional digits to identify whether the trade has a level, class, category, etc., also include these additional digits in this data element.
 
Size of Field: Maximum of 10 characters

Codes
N/A

Element No. 30: Trade code description

Description
The name of the trade reported as a trade code in the previous element no. 29 – Trade code.

Report the complete name of the trade and do not include short form abbreviations.

Size of Field: Maximum of 80 characters

Codes
N/A

Element No. 31: Level code

Description
If the trade code reported in element no. 29 – Trade code, includes additional digits to identify whether the trade has a level, class, category, etc., in this element just report the actual code for the level, class, category, etc.

Report for the registered apprentice and trade qualifier (challenger).

If not available, leave blank.

Size of Field: Maximum of 8 characters

Codes
N/A

Element No. 32: Level code description

Description
The name of the level, class, category, etc., reported in the previous element no. 31 – Level code.

Report the complete name of the level, class, category, etc., and do not include short form abbreviations.

Report for the registered apprentice and trade qualifier (challenger).

If not available, leave blank.

Size of Field: Maximum of 80 characters

Codes
N/A

Element No. 33: Program duration

Description
This element identifies the normal length of time required to complete the entire program and is usually expressed in years, periods or skills/competency levels.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 3 digits numeric

Codes
N/A

Element No. 34: Duration in hours for duration based programs

Description
Identifies the total overall program duration in hours (e.g. 8000) reported in the previous element no. 33 - Program duration.

Note: The hours reported apply to the normal overall program length in hours and should have the same hours for all records with the same trade reported in the previous element no. 29 – Trade code.
 
Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 35: Program duration units

Description
Identifies the type of unit used to measure the intervals over the duration of the program reported in element no. 33 - Program duration.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Years
2 – Periods
3 – Skills/Competency levels
4 – Program credits
9 – Unknown

Element No. 36: Competency or duration based program

Description
Identifies if the trade program is offered as a competency based program or a duration based program.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".
 
Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Duration based program
2 – Competency based program
3 – Duration and competency based program
9 – Unknown

Element No. 37: Compulsory or voluntary trade

Description
This element identifies if the trade is a compulsory certified trade or a voluntary certified trade.

Report for the registered apprentice and trade qualifier (challenger).

Size of Field: 1 digit numeric

Codes
1 – Compulsory
2 – Voluntary
3 – Compulsory and voluntary
9 – Unknown

Element No. 38: Registration status

Description
This element identifies the registration status of the apprentice at the beginning and during the reporting period.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Already registered (beginning of report period)
2 – New registration (during report period)
3 – Reinstatement (during report period)
9 – Unknown

Element No. 39: Date of registration

Description
This element identifies the date when the current contract or agreement of understanding between an apprentice and employer was registered with the jurisdiction.

Do not report for trade qualifier (challenger), leave blank.

Note: For this data element do not report any empty spaces, dashes or backslashes. Each field in this data element should be filled with a character (e.g. 03061985).

If not available, leave blank.

Size of Field: 8 digits numeric

Codes
DDMMYYYY (Day Month Year)

Element No. 40: Reinstatement date

Description
If a reinstatement has been reported for the apprentice in element no. 38 - Registration status, in this element identify the date of the reinstatement.

Do not report for trade qualifier (challenger), leave blank.

Note: For this data element do not report any empty spaces, dashes or backslashes. Each field in this data element should be filled with a character (e.g. 061985).

If not available, leave blank.

Size of Field: 6 digits numeric

Codes
MMYYYY (Month Year)

Element No. 41: Status at end of reporting period

Description
This element identifies the status of the apprentice during the reporting period and at the end of the reporting period.

When reporting information on apprentices that have successfully completed their programs and obtained their certificates, there can be a choice of three different types:

The first and most common, is identified below as a code = 2, and relates to the successful completion of an entire program, regardless of length, with a certificate granted after the entire program is completed.

The second and third types of successful completion are identified below by code = 3 and code = 4, and relate to certain programs which grant certificates after a segment of a longer extended program is completed. Examples of this type of completion are the Motor Vehicle Body Prepper and Motor Vehicle Body Refinisher programs, which are shorter in duration length, and designed as separate and partitioned programs of the extended Motor Vehicle Body Repairer program. These shorter programs usually allow an individual, after receiving their certificate, the choice of either continuing or not continuing their training in the extended program. Because of this choice, code = 4 is used to identify an individual who has decided to continue in the extended program of the trade, while code = 3 is used to identify an individual who has decided not to continue in the extended program of the trade.

Note: When reporting the successfully completed for programs which have been partitioned, do not relate this to the completion of an individual class or level found in some programs, which have divided their training into several classes or levels, such as the stationary engineer – 1st class, 2nd class, 3rd class, etc.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Continuing and still registered
2 – Successfully completed the entire program with a certificate granted
3 – Successfully completed a segment of an entire program with a certificate granted and not continuing in the trade
4 - Successfully completed a segment of an entire program with a certificate granted and still continuing in the trade
5 – Discontinued the program (cancelled, suspended, terminated, etc.)
6 – Transferred to another program
9 – Unknown

Element No. 42: Initial credits at registration

Description
In this element report the credits (either in hours, skill/competency levels or program credits) given for combined technical (in-class) training (obtained from colleges, high schools, commission scolaire or similar postsecondary and secondary institutions, etc.) and for on-the-job (work) training, prior to starting the apprenticeship program.

In the following element no. 43 – Type of initial credits at registration, report whether the credits are in hours, skill/competency levels or program credits.

Note: Only report this element if technical (in-class) training and on-the-job (work) training information cannot be reported separately as two elements in no. 44 - Technical training credits at registration and no. 46 - On-the-job training credits at registration.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 43: Type of initial credits at registration

Description
Report the type of credits identified in the previous element no. 42 - Initial credits at registration.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Hours
2 – Skill/competency levels
3 – Program credits
9 – Unknown

Element No. 44: Technical training credits at registration

Description
In this element report the credits (either in hours, skill/competency levels or program credits) given for technical (in-class) training or courses prior to starting the apprenticeship program.

In the following element no. 45 – Type of technical training credits at registration, report whether the credits are in hours, skill/competency levels or program credits.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 45: Type of technical training credits at registration

Description
Report the type of credits identified in the previous element no. 44 - Technical training credits at registration.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Hours
2 – Skill/competency levels
3 – Program credits
9 – Unknown

Element No. 46: On-the-job training credits at registration

Description
 In this element report the credits (either in hours, skill/competency levels or program credits) given for on-the-job (work) training prior to starting the apprenticeship program.

In the following element no. 47 – Type of on-the-job training credits at registration, report whether the credits are in hours, skill/competency levels or program credits.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 47: Type of on-the-job training credits at registration

Description
Report the type of credits identified in the previous element no. 46 - On-the-job training credits at registration

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Hours
2 – Skill/competency levels
3 – Program credits
9 – Unknown

Element No. 48: On-the-job hours completed to date for duration based programs

Description
If reporting levels or competencies for competency based programs, include this information in the next element no. 49 - Competency based on-the job levels completed to date.

In this element report the number of on-the-job (work) hours accumulated since the registration date. These completed hours should not include the on-the-job hours which may have been credited prior to registration and reported in the element no. 46 - On-the-job training credits at registration.

 Note: The hours completed should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 49: Competency based on-the job levels completed to date

Description
The number of accumulated on-the-job levels or competencies completed to date for competency based programs.

Note: The levels or competencies completed should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 3 digits numeric

Codes
N/A

Element No. 50: Competency based on-the job levels required

Description
This element identifies the total number of on-the-job levels or competencies required to complete the competency based program, and is requested if element no. 49 - Competency based on-the job levels completed to date is reported.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 3 digits numeric

Codes
N/A

Element No. 51: Date of latest recording of hours or levels completed to date

Description
In this element report the date of the latest recording of on-the-job hours completed to date, if element no. 48 - On-the-job hours completed to date for duration based programs or element no. 49 - Competency based on-the-job levels completed to date is being reported.

Note: The date of the latest recording should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Note: For this data element do not report any empty spaces, dashes or backslashes. Each field in this data element should be filled with a character (e.g. 061985).

If not available, leave blank.

Size of Field: 6 digits numeric

Codes
MMYYYY (Month Year)

Element No. 52: Technical levels or courses completed to date

Description
This element identifies the total number of technical (in-class) levels or courses completed by the apprentice out of the total number of levels or courses required for the program. These completed technical in-class levels or courses should not include the technical training time which may have been credited prior to registration and reported in the element no. 44 - Technical training credits at registration.

Note: These completed levels or courses apply to both duration and competency based programs and should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 2 digits numeric

Codes
N/A

Element No. 53: Technical hours completed to date

Description
In this element report the equivalent hours, related to the technical levels or courses completed and reported in the previous element no. 52 - Technical levels or courses completed to date.

In this element report the total number of technical (in-class) hours completed by the apprentice out of the total number of hours required for the program.

Note: The hours completed apply to both duration and competency based programs and should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 54: Number of technical levels or courses required

Description
This element identifies the total number of technical (in-class) levels or courses required to complete the program, and requested if element no. 52 - Technical levels or courses completed to date is reported.

Note: This element applies to both duration and competency based programs and should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 2 digits numeric

Codes
N/A

Element No. 55: Technical hours required

Description
Report the equivalent hours, if the number of technical levels or courses required was reported in the previous element no. 54 - Number of technical levels or courses required.

For this element report the total number of technical (in-class) hours required to complete the program.

Note: This element applies to both duration and competency based programs and, if required, should be up-dated every new reporting period.

Do not report for trade qualifier (challenger), leave blank.

Size of Field: 5 digits numeric

Codes
N/A

Element No. 56: Method/Mode of institutional training

Description
This element identifies the delivery type of technical training undertaken during the apprenticeship period being reported.

Do not report for trade qualifier (challenger); code as "00 – Not applicable".

Size of Field: 2 digits numeric

Codes
00 – Not applicable
01 – Block release
02 – Modular training
03 – Course based
04 – Day release
05 – Distance education
06 – Employer training
07 – Level
08 – Mobile
09 – Competency based apprenticeship training (CBAT)
10 – Weekly apprenticeship training (WATS)
11 – Other
99 – Unknown

Element No. 57: Full-time/Part-time status

Description
This element is linked to the previous element no. 56 - Method/Mode of institutional training, and identifies whether the training was either full-time or part-time.

Full-time training can be identified with an extended period of training like block release.

Do not report for trade qualifier (challenger); code as "0 – Not applicable".

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – Full-time
2 – Part-time
9 – Unknown

Element No. 58: Type of certificate of qualification granted

Description
This element identifies the type of certificate granted to the apprentice or trade qualifier (challenger).
 
Note: If the Certificate of Apprenticeship is the final certificate granted in the trade, and the Certificate of Qualification is not being granted, then report the Certificate of Apprenticeship. The granting of these certificates usually involves the completion and passing of a final exam.

Size of Field: 1 digit numeric

Codes
0 – Not applicable
1 – No certificate granted
2 – Certificate granted with a Red Seal endorsement to an apprentice (who has completed the final exam)
3 – Certificate granted without a Red Seal endorsement to an apprentice (who has completed the final exam)
4 – Certificate granted with a Red Seal endorsement to a trade qualifier (challenger)
5 – Certificate granted without a Red Seal endorsement to a trade qualifier (challenger)
6 – Certificate granted with a Red Seal endorsement to a journeyperson who previously completed an apprenticeship program and received a certificate without a Red Seal endorsement in the same trade
7 – Certificate granted with a Red Seal endorsement to a trade qualifier (challenger) who previously received a certificate without a Red Seal endorsement in the same trade
9 – Unknown

Element No. 59: Date of certification

Description
In this element report the date the certificate was granted to an apprentice or trade qualifier (challenger), if a certificate was reported in the previous element no. 58 - Type of certificate of qualification granted.

If a jurisdiction grants both a Certificate of Qualification and a Certificate of Apprenticeship, report only the Certificate of Qualification date in this element. However, if the Certificate of Apprenticeship is the final certificate granted in the trade, and the Certificate of Qualification is not being granted, then report the date the Certificate of Apprenticeship was granted.

Note: For this data element do not report any empty spaces, dashes or backslashes. Each field in this data element should be filled with a character (e.g. 03061985).

If not available, leave blank.

Size of Field: 8 digits numeric

Codes
DDMMYYYY (Day Month Year)

Element No. 60: Prior trade certificate

Description
This element identifies if the apprentice or trade qualifier (challenger) received a certificate in a previous trade, and granted in the current reporting jurisdiction or any other jurisdiction. The previous certification must be in a trade recognized in Canada.

If the apprentice or trade qualifier was certified in more than one trade, please report the latest trade in which they were certified.

The identifier for this previous trade is the trade code used by the jurisdiction.

Size of Field: Maximum of 10 characters

Codes
N/A

Element No. 61: Filler

Description
This element should be left empty and is for information which may be requested in the future.

Size of Field: Maximum of 100 characters

Codes
N/A

Elements Reserved for Statistics Canada

STC Element No. 1: RAIS Trade code

Description
This element is reserved for Statistics Canada to code and identify trades using a modified version of the National Occupational Classification (NOC) codes.

The trade code reported will be converted to the National Occupational Classification NOC+3 trade code (abcd.xx.yy.zz), where:

• The four digit NOC code (abcd) identifies the major occupational category;
• The first extension (xx) represents a distinct and separate trade;
• The second extension (yy) identifies subtrades of the distinct trade and;
• The third extension (zz) is used for further level/class/category distinctions within the trade.

Size of Field: 10 digits numeric

Codes
NOC+3

STC Element No. 2: Red Seal or non-Red Seal indicator

Description
Reserved for Statistics Canada to identify Red Seal or non-Red Seal trades.

The Red Seal trades are drawn from the list approved by the Canadian Council of Directors of Apprenticeship (CCDA).

Size of Field: 1 digit numeric

Codes
0 – Without inter-provincial standards
1 – Red Seal with inter-provincial standards

STC Element No. 3: Red Seal or non-Red Seal endorsement

Description
Used by Statistics Canada to identify if Red Seal or non-Red Seal endorsement is being granted by the jurisdictions.

This element will be derived by Statistics Canada using a combination of information from the data elements reported by the jurisdictions:

• STC Element no. 1 – RAIS Trade code
• Element no. 58 – Type of certificate of qualification granted

Size of Field: 1 digit numeric

Codes
1 – Only Red Seal endorsement granted
2 – Red Seal and non-Red Seal endorsement granted
3 – Only non-Red Seal endorsement granted
9 – Unknown

STC Element No. 4: Current year or period of the program

Description
Only for duration based programs, the current year or period of the program in which the apprentice is registered, based on the total accumulated technical and on-the-job training hours.

This element will be derived by Statistics Canada using a combination of information from the data elements reported by the jurisdictions:

• • Element no. 33 - Program duration (DURPGM)
  • Element no. 34 - Duration in hours for duration based program (DURHOURS)
  • Element no. 35 - Program duration units (DURUNITS)
  • Element no. 42 - Initial credits at registration (INICREDR)
  • Element no. 48 - On-the-job hours completed to date for duration based program (JOBHCOMP)
  • Element no. 53 - Technical hours completed to date (TECHCOMP)

Current year or period of the program =

[DURPGM] – [DURHOURS – INICREDR – JOBHCOMP – TECHCOMP] * DURPGM / DURHOURS

Size of Field: 1 digit numeric BIRTHY

Codes
N/A

STC Element No. 5: Age in years

Description
Used by Statistics Canada to derive the age in years of the apprentice or trade qualifier (challenger).

This element will be derived by Statistics Canada using information reported by the jurisdictions:

• Element no. 1 - Reporting year (REPYR)
• Birth year (BIRTHY) from element no. 21 – Date of birth

Age in years = REPYR –

Size of Field: 2 digits numeric

Codes
N/A

STC Element No. 6: Input type

Description
Used by Statistics Canada to identify whether the jurisdiction is reporting individual record data or aggregate information.

Size of Field: 1 digit numeric

Codes
1 – Individual
2 – Aggregate

STC Element No. 7: Certificate or registration indicator

Description
Used by Statistics Canada to identify whether a registration file or a certificate file.

Size of Field: 1 digit numeric

Codes
1 – Registration
2 – Certificate

STC Element No. 8: Previous apprenticeship training - RAIS Trade code

Description
This element is reserved for Statistics Canada to code and identify trades using a modified version of the National Occupational Classification (NOC) codes.

The trade code reported will be converted to the National Occupational Classification NOC+3 trade code (abcd.xx.yy.zz), where:

• The four digit NOC code (abcd) identifies the major occupational category;
• The first extension (xx) represents a distinct and separate trade;
• The second extension (yy) identifies subtrades of the distinct trade and;
• The third extension (zz) is used for further level/class/category distinctions within the trade.

Size of Field: 10 digits numeric

Codes
NOC+3

STC Element No. 9: Prior trade certificate - RAIS Trade code

Description
This element is reserved for Statistics Canada to code and identify trades using a modified version of the National Occupational Classification (NOC) codes.

The trade code reported will be converted to the National Occupational Classification NOC+3 trade code (abcd.xx.yy.zz), where:

• The four digit NOC code (abcd) identifies the major occupational category;
• The first extension (xx) represents a distinct and separate trade;
• The second extension (yy) identifies subtrades of the distinct trade and;
• The third extension (zz) is used for further level/class/category distinctions within the trade.

Size of Field: 10 digits numeric

Codes
NOC+3

Notes

1. Mandatory elements
2. Do not report for trade qualifiers (challengers)
3. Jurisdictions are not asked to report these elements – reserved for Statistics Canada
4. Element no. 42 – Initial credits at registration (INICREDR) will be substituted by both, element no. 44 - Technical training credits at registration
5. (TECCREDR) and element no. 46 - On-the-job training credits at registration (JOBCREDR), if technical and on-the-job credits at registration can be reported separately by the jurisdictions.

Purchased from Manitoba producers

• Report for the month of

Confidential when completed. This survey is conducted under the authority of the Statistics Act, Revised Statutes of Canada, 1985, c. S-19. Completion of this questionnaire is a legal requirement under the Statistics Act.

The purpose of this survey is to collect reliable and up-to-date information on non-board grains and specialty crops in the province of Manitoba. These data are used to calculate farm cash receipts which measure agriculture contribution to the Canadian economy. The data are also used by producer organizations, government departments and others for policy and decision-making.

Please provide the information requested on non-board grains and specialty crops for the month specified.

• tonnes purchased (dockage and shrinkage deducted)
• gross receipts (only rail freight and elevation deducted)

In compiling average provincial prices to producers, your data will be aggregated with data received from other companies to protect the confidentiality.

Please return your completed questionnaire by facsimile to (613) 951-3868. If you have any questions, please telephone Gail-Ann Breese (204) 983-3445. Thank you

1. Tonnes Purchased
2. $ Paid to Producers

• Wheat
• Oats
• Barley for feed
• Barley for malting
• Rye
• Flaxseed
• Canola
• Dry Field Peas
• Buckwheat
• Sunflower Seeds
• Corn for grain
• Canary seed
• Fababeans
• Lentils
• Dry Beans
• Triticale
• Mustard Seed
• Chickpeas
• Soybeans

General information

Confidentiality

Your answers are confidential.

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. The confidentiality provisions of the Statistics Act are not affected by either the Access to Information Act or any other legislation. Therefore, for example, the Canada Revenue Agency cannot access identifiable survey records from Statistics Canada.

Information from this survey will be used for statistical purposes only and will be published in aggregate form only.

Record linkages

To enhance the data from this survey, Statistics Canada may combine it with information from other surveys or from administrative sources.

Data-sharing agreements

To avoid duplication of enquiry, Statistics Canada has entered into data-sharing agreements with provincial statistical agencies, which must keep the data confidential and use them only for statistical purposes. Statistics Canada will only share data from this survey with those organizations that have demonstrated a requirement to use the data.

Section 11 of the Statistics Act provides for the sharing of information with provincial statistical agencies that meet certain conditions. These agencies must have the legislative authority to collect the same information, on a mandatory basis, and the legislation must provide substantially the same provisions for confidentiality and penalties for disclosure of confidential information as the Statistics Act. Because these agencies have the legal authority to compel businesses to provide the same information, consent is not requested and farm operations may not object to the sharing of their data.

For this survey, there are Section 11 agreements with the provincial statistical agencies of Manitoba, Saskatchewan and Alberta.

The shared data will be limited to information pertaining to farm operations located within the jurisdiction of the respective province.

Fax or other electronic transmission disclosure

There could be a risk of disclosure during the facsimile or electronic transmission. However, upon receipt of your information, Statistics Canada will provide the level of protection afforded for all information collected under the authority of the Statistics Act.