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 2012 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

Concept Review

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 2012 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 2012, followed by a six-month parallel run (from reference month September 2012 to reference month February 2013). The refreshed sample officially became the new sample of the MSM effective in December 2012.

This marks the first process of refreshing the MSM sample since 2007. The objective of the process is to keep the sample frame as fresh and up-to date as possible. All establishments in the sample are refreshed to take into account changes in their value of sales of goods manufactured, the removal of dead units from the sample and some small units are rotated out of the GST-based portion of the sample, while others are rotated into the sample.

Prior to selection, the sampling frame is subdivided into industry-province cells. For the most part, NAICS codes were used. Depending upon the number of establishments within each cell, further subdivisions were made to group similar sized establishments’ together (called stratum). An establishment’s size was based on its most recently available annual sales of goods manufactured or sales value.

Each industry by province cell has a ‘take-all’ stratum composed of establishments sampled each month with certainty. This ‘take-all’ stratum is composed of establishments that are the largest statistical enterprises, and have the largest impact on estimates within a particular industry by province cell. These large statistical enterprises comprise 45% of the national manufacturing sales of goods manufactured estimates.

Each industry by province cell can have at most three ‘take-some’ strata. Not all establishments within these stratums need to be sampled with certainty. A random sample is drawn from the remaining strata. The responses from these sampled establishments are weighted according to the inverse of their probability of selection. In cells with take-some portion, a minimum sample of 10 was imposed to increase stability.

The take-none portion of the sample is now estimated from administrative data and as a result, 100% of the sample universe is covered. Estimation of the take-none portion also improved efficiency as a larger take-none portion was delineated and the sample could be used more efficiently on the smaller sampled portion of the frame.

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.

Effective from the January 2013 reference month, the MSM derives sales of goods manufactured data for non-incorporated establishments (e.g. the self employed) from T1 files. A statistical model is used to transform T1 data into sales of goods manufactured data.

In conjunction with the most recent sample, effective December 2012, approximately 2,800 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 2,800 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 2006-2007 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 December 2012 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.

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.

Sources of non-sampling error in the MSM include non-response error, imputation error and the error due to editing. To assist users in evaluating these errors, weighted rates 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 for the weighted rates noted in Text table 2 follow. The weighted response and edited rate is the proportion of a characteristic’s total estimate that is based upon reported data and includes 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 GST data rate is the proportion of the characteristic’s total estimate that is derived from Goods and Services Tax files (GST files). The weighted take-none fraction rate is the proportion of the characteristic’s total estimate modeled from administrative data.

Text table 2 contains the 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 X12-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 2007. The resulting deflated values are said to be “at 2007 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 2007. This is called the base year. The year 2007 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.

Statistics Canada’s main campus is in the National Capital Region (Ottawa-Gatineau)

The National Capital Region is one of the most desirable places to live in the world. Once you discover its dynamic culture, distinctive neighbourhoods, family-friendly atmosphere, bustling arts and entertainment scene, and countless recreational options, we think you’ll agree that this is truly a special place.

Neighbourhoods

One of the most important decisions you will have to make is choosing where to live. There are dozens of desirable neighbourhoods in the National Capital Region, for example:

The Downtown Ottawa area is a mix of residential and commercial neighbourhoods. Within this area you will find the Glebe, one of the oldest and most elegant areas of Ottawa, Centretown, housing many young professionals in its numerous high-rises, and Preston Street, which is the heart of the Italian community.

Riverside is a newer neighbourhood, located in the south end of the city. Although it is only fifteen minutes from downtown, there are hundreds of acres of parks and numerous nature trails in Riverside.

Westboro is a thriving community located along the Ottawa River. With its gentrified older homes and an increasingly lively street scene, Westboro is establishing itself as a popular destination for food, shopping and nightlife.

Kanata is a popular suburban area in the west end of Ottawa. It is a planned community, and it is notable for being an important high-tech centre. Kanata is located about 22 kilometres west of downtown Ottawa along Highway 417.

Orleans is one of Ottawa’s fastest growing suburban areas. Not only does it boast a large shopping centre, but there is also plenty of recreational space. The community is about 16 kilometres east of Ottawa’s downtown core, just a ten minute drive away.

Gatineau is a city in West Quebec, situated immediately across the Ottawa River, opposite the City of Ottawa. Prior to 2002, there were five cities on the Quebec side of the Ottawa River: Hull, Gatineau, Aylmer, Buckingham and Masson-Angers. These amalgamated into one city, and the remaining four communities have now become suburbs or neighbourhoods. As part of the National Capital Region, Ottawa and Gatineau make up a single Metropolitan Area.

There are major tourist attractions in Gatineau, such as the Canadian Museum of Civilization and the Casino du Lac Leamy.

Each Labour Day weekend, Gatineau hosts a hot air balloon festival, filling the skies over the city with hundreds of colourful balloons.

One of Gatineau’s larger parks, Jacques Cartier Park, is used by the National Capital Commission each February during the popular outdoor festival, Winterlude.

Without a doubt, the National Capital Region’s jewel is Gatineau Park. Only 15 minutes from Parliament Hill, the Park is endowed with hundreds of hiking trails through forests containing more than fifty species of trees, abundant wildlife and several crystal-clear lakes. During the summer, visitors can participate in outdoor activities such as hiking, cycling, swimming and camping, and in the winter months, they can ski or snowshoe on the more than 200 kilometres of groomed paths.

Of course, these are only a few of the lovely neighbourhoods found in the National Capital Region. There are many more, each with its own personality.

Gain valuable work experience in your field of study at Statistics Canada. Check out these three popular programs. One of them might be perfect for you:

Co-op / Internship

Interested in short-term employment in a federal organization? Gain relevant and practical work experience over a four-month co-op or internship. Here’s what you need to do:

• Consult the notice boards at your campus career centre or co-op/internship placement office. If any of the posted opportunities seem like a good fit with your study/career ambitions, then register in a co-op/internship program with your academic institution.
• You won’t find a listing of co-op/internship opportunities on the Public Service Commission’s website. Federal organizations that wish to hire students for co-op/internship placements will contact the educational institutions directly to place their request.

For more information, visit the Co-op/Internship program.

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• 2022-09-01
  Police-Reported Racialized and Indigenous Identity Statistics via the Uniform Crime Reporting Survey: Report and Draft Recommendations
• 2022-08-10
  Statistics Canada to hold news conference to present 2021 Census data on linguistic diversity and the use of English and French in Canada
• 2022-08-10
  Backgrounder: 2021 Census of Population - linguistic diversity and the use of English and French in Canada
• 2022-07-08
  Statistics Canada to hold news conference to present 2021 Census data on families, military experience and income
• 2022-07-06
  Backgrounder: 2021 Census of Population
• 2022-05-03
  Statistics Canada and Mila partner to advance ethical artificial intelligence and machine learning development
• 2022-03-31
  Statistics Canada to hold news conference to present 2021 Census data on Canada's shifting demographic profile
• 2022-02-07
  Reminder – Statistics Canada to hold a news conference to present highlights of first 2021 Census release
• 2022-02-02
  2021 Census of Population – Backgrounder for Media
• 2022-01-13
  Statistics Canada to hold a news conference to present highlights of first 2021 Census release
• 2021-12-16
  Statement on the release of the Canadian Statistics Advisory Council's second Annual Report
• 2021-11-18
  Statistics Canada thanks Canadians for their contribution to the 2021 Census
• 2021-06-10
  2021 Census: Enumerators now following up with dwellings
• 2021-05-20
  Census: Enumerators to begin follow-ups with dwellings
• 2021-05-03
  The 2021 Census of Population and Census of Agriculture begin today!
• 2021-04-06
  Backgrounder for the 2021 Census
• 2021-03-23
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  Statistics Canada staffing 32,000 census jobs across Canada

Program adjustments by sector

Aboriginal Statistics

Aboriginal Statistical Training Program
The end of the Aboriginal Statistical Training Program was announced on May 16, 2012. The course material is available upon request.

Agriculture

Agriculture Value Added Account
The final release of the Agriculture Value Added Account was published on November 24, 2011. Custom data tables on the Agriculture Value Added Account continue to be available on a cost-recovery basis from the Agriculture Economic Statistics Program.

Farm Business Cash Flows
The final release of the Farm Business Cash Flows was published on January 18, 2012. Custom data tables on the Farm Business Cash Flows continue to be available on a cost-recovery basis from the Agriculture Economic Statistics program.

Farm Cash Receipts
Effective May 23, 2012, farm cash receipts data are released semi-annually instead of quarterly. Data for the second and third quarters of 2012 will be released in November 2012. Information on net farm income for 2011 will also be released in November 2012.

Farm Product Price Index
Effective June 2012, the Farm Product Price Index has been released quarterly instead of monthly. The most recent release took place on June 4, 2012. The next release of the Index will be on August 29, 2012.

Farm Product Prices Survey
The following four components of the survey are discontinued: Potato prices; Straw and hay prices; Grain and oilseed prices; Grain and specialty crop prices. Statistics Canada is investigating ways to replace these price components with administrative sources. All other components of the Farm Product Prices Survey will continue to be published.

Field Crop Reporting Series: The December Farm Survey
The last release of the December Farm Survey was on February 3, 2012. Other surveys in the Field Crop Reporting Series will continue to be conducted.

Fruit and Vegetable Survey
Starting in 2013, Statistics Canada will release data from the Fruit and Vegetable Survey once a year instead of twice a year. The spring data collection has been discontinued. The last available results of the Spring Fruit and Vegetable Survey were published on June 23, 2011. The fall data collection will continue, with results for reference year 2012 to be published in early 2013.

Hog Survey
Starting with the July 2012 occasion, data for the Hog Survey will be collected twice a year instead of quarterly. Data for the July and January reference periods will continue to be collected while the October and April collections have been discontinued. Information will continue to be published from the January and July surveys.

Net Farm Income
Statistics Canada will release data on net farm income once a year instead of twice a year. As a result, the release of preliminary data for net farm income for 2011, scheduled for May 23, 2012, was cancelled. Data for 2011 will be released on November 26, 2012.

Culture

Surveys of Government Expenditures on Culture
The elimination of two surveys of government expenditures on culture was announced on May 17, 2012. Information on culture continues to be available through other Statistics Canada programs such as the Labour Force Survey, the Census Program and some service industries' surveys.

Economy – General

Composite Leading Indicator
Statistics Canada published the last release of data for the Composite Leading Indicator on May 23, 2012. Similar information is available from other sources, in particular the Organization for Economic Co-operation and Development, which publishes more up-to-date leading indicators for Canada and other member nations.

Education

Education Matters: Insights on Education, Learning and Training in Canada
The final issue of Education Matters: Insights on Education, Learning and Training in Canada was released on May 1, 2012. In future, analytical articles on education themes will be published directly on Statistics Canada's website.

Salaries and Salary Scales of Full-time Teaching Staff at Canadian Universities
The final issue of Salaries and Salary Scales of Full-time Teaching Staff at Canadian Universities was released on May 3, 2012. The Full-time University and College Academic Staff Survey has been discontinued.

Energy

Annual Coal Mines Survey
The last release of the Annual Coal Mines Survey was on May 4, 2012. The survey has been discontinued.

Annual Contract Drilling and Services to Oil and Gas Extraction Survey
The last direct release of the Annual Contract Drilling and Services to Oil and Gas Extraction Survey took place on March 17, 2008. Since then, the data have continued to be used as an input into products of the System of National Accounts and made available to the public through the release of those products. The survey was discontinued on April 1, 2012.

Annual Electricity Utility Financial Survey
The last release of information from the Annual Electricity Utility Financial Survey was on February 2, 2012. The survey has been discontinued.

Annual Gas Utilities/Transport and Distribution Survey
The last release from the Annual Gas Utilities/Transport and Distribution Survey took place on March 12, 2008. Since then, the data have continued to be used as an input into products of the System of National Accounts and made available to the public through the release of those products. The survey was discontinued on April 1, 2012.

Annual Oil Pipeline Transport Survey
Statistics Canada published the last release of the Annual Oil Pipeline Transport Survey on March 12, 2008. Since then, the data have continued to be used as an input into products of the System of National Accounts and made available to the public through the release of those products. The survey was discontinued on April 1, 2012.

Health

Residential Care Facilities
The final release of the Residential Care Facilities Survey was published on July 17th, 2012. The program is discontinued.

Labour and Income

Survey of Labour and Income Dynamics
The final release of longitudinal data from the Survey of Labour and Income Dynamics was published on June 18, 2012. Statistics Canada will continue to conduct a survey to produce annual estimates on income.

Non-profit Sector

Satellite account of non-profit institutions and volunteering
The last release of the Satellite account of non-profit institutions and volunteering was in December 2010. This program has been discontinued, however, as part of the Canadian System of National Accounts historical revision (2012) a portion of this account will be published on a quarterly basis, specifically the activities of non-profit institutions serving households. Statistics Canada will publish a paper outlining how users can construct estimates of the non-profit sector account using data from Statistics Canada.

Public Sector Statistics

Public Sector Employment Program
The final release of the Public sector employment program was published on May 30, 2012. Statistics Canada continues to produce data on public administration employment through the Survey of Employment, Payrolls and Hours and the Labour Force Survey.

Science and Technology

Provincial Scientific Activity Surveys
Statistics Canada is ending its contribution to a number of provincial surveys that measure scientific activities by provincial governments. The final release is currently planned for the end of the summer of 2012.

Survey of Federal Intellectual Property Management
The final release of the Federal Intellectual Property Management Survey was on May 16, 2012. The survey has been discontinued.

Survey of Intellectual Property and Commercialization in the Higher Education Sector
The final release of this survey is currently planned for the end of the summer of 2012. The survey has been discontinued.

Service Industries

Annual Survey of Service Industries: Personal Services
Statistics Canada published the last release of data from this survey on February 28, 2012. The survey has been discontinued.

Quarterly Industry Revenue Indices
Statistics Canada published the last release of data from this survey on March 28, 2012. The survey has been discontinued.

Transport

Air Carrier Operations in Canada Survey (Civil Aviation Surveys)
Statistics Canada will continue to publish the same information from the Air Carrier Operations in Canada Survey. However, the information will be released 20 months after the reference period instead of 14 months.

Air Passenger Origin and Destination, Canada – U.S.A.
The same data will continue to be published on air passenger origin and destination between Canada and the U.S. However, the information will be released 20 months after the reference period instead of 14 months.

Annual and Quarterly Trucking Surveys
Information collected with trucking surveys were last released on February 16, 2012 and April 3, 2012. Both surveys have been discontinued.

Fare Basis Survey
The same data will continue to be collected and published for the Fare Basis Survey. However, the information will be released 20 months after the reference period instead of 14 months.

Marine Origin and Destination Survey
The final release of the Marine Origin and Destination of Commodity Shipments Survey was published on April 26, 2012. The survey has been discontinued.

New Motor Vehicle Sales Survey
The last release of the monthly New Motor Vehicle Sales in its current format was on April 17, 2012. Effective on May 14, 2012, with the release of data for the March 2012 reference month, only unadjusted data on new motor vehicle sales are available. The unadjusted data continue to be available on CANSIM.

Program adjustments across sectors

Efficiencies through increased use of electronic data collection

Statistics Canada will continue its migration to electronic data collection for a number of business and household surveys. Increasing the use of online collection improves the cost-effectiveness of programs and provides respondents with an easy, accessible way to complete surveys.

Streamlining dissemination of publications

Statistics Canada is developing an innovative, web-based approach to releasing publications and analytical reports. This new approach will reduce the number of print publications to make analytical products accessible online to Canadians in a more timely fashion, at no charge.

Microdata linkage is an internationally recognized statistical method that maximizes the use of information to shed light on societal and economic questions. In particular, microdata linkage brings together information about an entity from two or more sources to form a combined microdata file about that same entity. This activity is conducted in accordance with Statistics Canada's Directive on Microdata Linkage, which has been in place since 1986.

Statistics Canada performs microdata linkages for the following purposes:

• to support the design, maintenance, evaluation, research and redesign of ongoing data collection and methodological studies within Statistics Canada
• to provide statistical information in aggregate or anonymous format in support of research studies.

As part of its governance over microdata linkages, Statistics Canada has pre-approved specific types of linkages. The linkages involved are those where the privacy risks and situations of potential conflict of interest are low and where procedures to mitigate risk to confidentiality and privacy are in place.

All other microdata linkages must undergo a prescribed review and approval process, which involves the submission of documented proposals to senior management. When such linkages include personal information, a summary of the approved microdata linkage is posted on Statistics Canada's website.

If you have any questions about microdata linkage, please contact the Departmental Privacy Officer at the following address:

Pierre Desrochers
Departmental Privacy Officer
Office of Privacy Management and Information Coordination
Strategic Data Management Field
Statistics Canada / Government of Canada
Pierre.Desrochers@statcan.gc.ca / Tel: 613-894-4086

• 2014 General Social Survey on Victimization: linking tax data from the T1 Personal File and T4 Summary and Supplementary file (075-2013, 040-2015)
• Evaluation of the Canada Child Tax Benefit (CCTB) file for the production of interprovincial migration estimates. (027-2013)
• Analysis of the change in Aboriginal identity reporting (026-2013)
• Life After Service Income Study: Linkage of a cohort of former Canadian Armed Forces members to tax information
• Linkage of the 2008 General Social Survey (GSS) Cycle 22, Social Networks, and the Longitudinal Immigrant Database
• Re-contact with the Justice system
• Study of the Gross Flows Into and Out of Particular Industries in New Brunswick, 2000 to 2011
• Amendment: Data linkage to examine pathways of Information and Communication Technology (ICT) students through post-secondary education (PSE) and into the labour market, 1998-2011 (057-2013)
• The Effectiveness of the Department of Foreign Affairs and International Trade and Development's Trade Commissioner Services (072-2013)
• The Importance of Governance Structures on Firm Performance in the Portfolio of Firms Receiving Support from the Business Development Bank of Canada (071-2013)
• Linking Data from the 2012 Survey of Financial Security to income tax Records file (T1)
• 2011 National Household Survey and Immigrant Landing File linkage
• 2012 Aboriginal Peoples Survey and 2011 National Household Survey Linkage
• 2012 Canadian Survey on Disability and 2011 National Household Survey Linkage
• Update: Gross Flows of Workers Into and Out of Industries in Newfoundland and Labrador, 2000 to 2011
• Examination of Sentencing Trends for Drug Offences and Motor Vehicle Theft to Revise the Crime Severity Index Weights
• Analysis of the legal components involved in self-identification among First Nations peoples
• Atlantic Canada Opportunities Agency (ACOA) – Update of Business Performance Evaluation Report (2010)
• Analyzing the differences in self-identification on the Census and Aboriginal Peoples Survey
• Canadian Employer-Employee Dynamics Database
• Long Term Income and Employment Among Breast Cancer Survivors: Linkage of British Columbia Breast Cancer Data and the Longitudinal Administrative Databank
• Amendment to Canada Student Loans Program Linkage to the Longitudinal Administrative Databank (CSLP-LAD)
• Expanding the Longitudinal Analytical Databank (LAD) to include Tax Free Savings Account (TFSA) information
• Update: Gross Flows of Workers Into and Out of Industries in Newfoundland and Labrador, 2000 to 2010
• Economic Development Agency of Canada for the Regions of Quebec (EDAC): Economic Impact – 2001 to 2010
• Linkage of Survey of Intellectual Property Management (SIPM) 2010 to the Linkable File Environment (LFE)

2014 General Social Survey on Victimization: linking tax data from the T1 Personal File and T4 Summary and Supplementary file (075-2013, 040-2015)

Purpose: The General Social Survey (GSS) program, established in 1985, conducts telephone surveys from a sample selected across the 10 provinces. Population in Yukon, Northwest Territories and Nunavut are not usually part of the targeted GSS population with the exception of cycles on victimization. The GSS is recognized for its regular collection of cross-sectional data that allows for trend analysis, and its capacity to test and develop new concepts that address emerging issues. Each year the GSS focuses on a different topic, such as family, victimization, social support and aging, and time use. A specific topic is usually repeated approximately every 5 years. The 2014 GSS which will focus on Victimization is the sixth iteration.

This survey is an important source of information to better understand how safe people feel, what they think of the justice system and their experiences of crime.

By linking the 2014 GSS on victimization responses to personal tax files of respondents, and the tax files of all household members, more accurate income (personal and household) information will be obtained for respondents. At the same time, response burden will be minimized, and collection, data processing, and testing costs will be reduced.

Description: The 2014 GSS on Victimization is a sample based survey with a cross-sectional design. Telephone surveys are conducted through computer assisted telephone interviews from a sample selected across the 10 Canadian provinces and interviews are conducted through a mix of computer assisted telephone interviews and computer assisted personal interviews in the territories. By linking data, we are aiming to obtain better quality data for income (personal and household).

Questions relating to income show rather high non-response rates, the incomes reported by respondents are usually rough estimates. Linking will allow getting such information without having to ask questions.

The information collected during the 2014 GSS on Victimization will be linked to the personal tax records (T1 or T4) of respondents, and tax records of all household members. Household information (address, postal code, and telephone number), respondent's information (social insurance number, surname, name, date of birth/age, sex) and information on other members of the household (surname, name, age, sex and relationship to respondent) will be key variables for the linkage.

Respondents will be notified of the planned linkage before and during the survey. Any respondents who object to the linkage of their data will have their objections recorded, and no linkage to their tax data will take place.

Output: The availability of the 2014 GSS on Victimization analytical aggregated data file will be announced in The Daily. The analysis file containing only aggregated data created using confidentiality procedures as required by Statistics Canada's directives will be made available to Statistics Canada researchers, and to deemed employees at the Statistics Canada Research Data Centres. All data will remain confidential and protected under the Statistics Act.

Along with the availability announcement of the analytical data file (in The Daily), only non-confidential aggregate statistics will be released.

Evaluation of the Canada Child Tax Benefit (CCTB) file for the production of interprovincial migration estimates. (027-2013)

Purpose: Preliminary interprovincial migration is estimated using a mathematical model based on Canada Child Tax Benefit (CCTB) data. This fiscal program, administered by the Canada Revenue Agency (CRA), helps families with the cost of raising children. Interprovincial migrants are defined as children whose parents' address changes (change of province) between two points in time. This is why it is critical that the CCTB addresses be of good quality, in other words, that they actually represent the child's place of residence and that they are quickly updated after a move.

The objective of linkage is therefore to assess the quality of the CCTB addresses by matching the data in that file with the 2011 Census data and the National Household Survey data. It ties in with both the evaluation of the quality of population estimates and the development of new methods.

Population estimates are the cornerstone of statistical measurement of the population. They are also used to calculate income transfers and cost-sharing programs between the different levels of government and to weight a number of Statistics Canada surveys. Furthermore, interprovincial migration is one of the components that best explains inaccuracies in the population estimates. Because linkage can evaluate the quality of the CCTB addresses, it is part of the population estimate quality evaluation process.

Description: The linked files are the 2011 CCTB monthly data, the 2011 Census data and the 2011 NHS data. Linkage was done deterministically by successive waves based on the following variables: last name, given name, date of birth, sex. The address, postal code and telephone number were used to evaluate the linkage quality. The linking key between the census and the NHS is the key created by the census team using the variables frame_id and persnr.

Output: The linked files, identifiers and linking keys will be kept until no longer required, up to, April 1, 2017, at which time they will be destroyed. Non-confidential aggregated results will be used in a presentation to the 2013 Methodology Symposium and in the symposium's written proceedings.

Analysis of the change in Aboriginal identity reporting (026-2013)

(Note that this will entail a secondary use of an approved linkage (026-2013). - R. Cunningham)

Purpose: The increased number of people reporting Aboriginal identity is a known phenomenon not only in Canada (Guimond, Robitaille and Sénécal 2003; Guimond 1999, 2003; Guimond, Kerr and Beaujot 2004; Siggner 2003; Caron-Malenfant et al. 2014) but also in the United States (Passel 1996, 1997; Eschbach 1993). This phenomenon necessarily leads to the conclusion that people change their reported status from one census to another. By combining census data with data from the Aboriginal Peoples Survey (APS) for the same individuals, it is possible to better understand this phenomenon by analyzing the factors associated with the fact that people change their self-reported identification over a very short period, specifically the time between the Census and the APS. It is even more important to understand it because studies on Aboriginal people depend on these responses and consider them to be "error-free".

We analyzed the change in Aboriginal identity reporting—inconsistencies in identifications by survey—by linking data from the 2006 Census with data from the 2006 APS, which enabled us to determine the scope of the phenomenon. In Canada, a significant proportion of the people living off reserve, who identified as First Nations or as Métis on the APS, did not report the same identity on the Census. In Quebec and Eastern Canada, the proportion is even greater.

Therefore, the purpose of the second phase of this study is to further our understanding of Aboriginal identification and, more specifically, the individual characteristics and contexts (province, region, municipality, among others) that are linked to the change in responses. In this phase, the 2011 data will be analyzed and the new results will be compared with the previous ones. The new results will also be used to review the results of analyses carried out using the identification criteria from only the Census or the APS to examine the situation of Aboriginal people.

Description: We would like to have access to a file containing the identity variables from the 2011National Household Survey (NHS), in addition to the 2012 APS data, for the same individuals. These variables (Aboriginal ancestry (Indian, Métis or Inuit), Aboriginal identity, registered Indian status, band membership, band identification) will enable us to validate the analyses of the 2006 data to determine whether the phenomenon is still as strong and has the same determining factors. Furthermore, we require access to the variable indicating the APS respondent's rank in the household. We need to know whether the APS respondent is Person 1 on the NHS—and therefore whether this person likely reported the first identification—or whether it was reported by a third party. We will do profile and classification analyses to validate the eight classes found in the 2006 analysis, then we will replicate the ordinary/logistic and multi‑level regression analyses (taking into account community of residence).

Output: Only aggregate or modelled statistics and analyses conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada.

Statistics Canada will retain the linked files for five years, until August 30, 2019, or until they are no longer required, at which time the said files will be destroyed.

Life After Service Income Study: Linkage of a cohort of former Canadian Armed Forces members to tax information

Purpose: To assess the economic outcomes of former Canadian Armed Forces (CAF) members after their release to civilian life. There are currently an estimated 594,500 CAF Veterans (regular and reserve force) and about 95,000 CAF members (68,000 regular force and 27,000 reserve force). Only about 11% of this population is currently receiving benefits and services from Veterans Affairs Canada (VAC). Transition outcomes are of interest to both Department of National Defence (DND) and VAC. This linkage will assist DND and VAC in identifying gaps in programs and services, evaluating existing programs and developing new re-integration and rehabilitation programs that meet the needs of military personnel as they transition to civilian life.

In addition, the New Veterans' Charter, which represents the most significant overhaul of rehabilitation and reintegration programs and services for veterans since the Second World War, was implemented by VAC in 2006 and both departments require more information on the impact of the new charter.

Description: Statistics Canada will provide indicators on the income of members released from the CAF from 1998 to 2010. Economic adjustment will be measured through the production of statistical tables from personal income tax data (T1 Family File (T1FF)) linked to a cohort of approximately 85,500 former CAF regular and reserve members whose personal identifiers and other key pre- and post- release status variables will be supplied by DND/VAC.

Output: Statistics Canada will prepare a set of analytical tables on the pre- and post-release incomes of veterans. Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released to VAC from the DND/VAC cohort linkage to T1FF. Information will be provided in tabular form. The client will not have direct access to the linked file. All access to this linked file will be restricted to employees of Statistics Canada whose work activities require access.

Linkage of the 2008 General Social Survey (GSS) Cycle 22, Social Networks, and the Longitudinal Immigrant Database

Purpose: A record linkage between the 2008 General Social Survey (GSS) on Social Networks and the Citizenship and Immigration Canada (CIC) Longitudinal Immigrant Database (IMD) would permit analysis of social outcomes (such as civic participation) of immigrants to Canada by entrance characteristics such as admission category (e.g. refugee, family class, etc.). The results from this record linkage would be used by Citizenship and Immigration Canada to support and evaluate immigrant policies and programs.

Description: The General Social Survey (GSS) on Social Networks provides detailed information on the social and civic integration of immigrants and ethno-cultural minorities into Canadian society. The Longitudinal Immigrant Database (IMDB) provides information on immigrants to Canada from 1980–2011 such as admission category and Low Income Measures.

The record linkage between the Landing File and the 2008 General Social Survey employed a hierarchical deterministic record linkage program developed by HSMD for the IMDB.

Only GSS respondents will be maintained for this record linkage.

Output: Only aggregate statistical estimates that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Outputs for the Longitudinal Immigrant Database (IMDB) and the General Social Survey (GSS) on Social Networks linkage will include a collection of cross-tabulations between these two sources.

The linkage results including variables used to perform the record linkage such as personal identifiers and information used to measure the linkage quality will be destroyed by March 31, 2014, or sooner if no longer required. All files will be kept on a server in a secure area. Access to these files is restricted to Statistics Canada employees whose assigned work activities require such access.

Re-contact with the Justice system

Purpose: To determine the types of unique information required to create and support high quality indicators of re-contact within the policing sector of justice. Whereas contact is defined as a documented official intervention (e.g. charge) against a person by a criminal justice agency/organization, a re-contact is defined as a subsequent contact signifying a new, official intervention by the agency/organization during a specified follow-up period.

The proposed project will attempt to establish baseline metrics on re-contact with policing sector and can serve as a comparison group for the previous policing re-contact evaluation undertaken in record linkage 065-2012. It will also provide the potential to be able to track emerging patterns of re-contact which may appear to be unique within a jurisdiction at a local level yet are more systematic in nature when evaluated at a higher level (e.g. national) of analysis.

Description: The proposed project consists of one record linkage activity which will be used to support the development of re-contact indicators within the policing sector of justice.

The linkage will use records collected under the Uniform Crime Reporting Survey (UCR2), in addition to supplemental personal identifiers provided by the Waterloo Regional Police Service for the years January 1, 2005 to December 31, 2011.

Output: Only aggregate statistics and analyses conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Access to linking keys and linked analysis file will be restricted to Statistics Canada employees whose assigned work activities require such access.

High-level findings may be reported in the form of presentations to various National Justice Statistics Initiative partners.

Statistics Canada will retain the linked analysis files until March 31, 2017 or sooner if no longer required, at which time the linked analysis files will be destroyed.

Study of the Gross Flows Into and Out of Particular Industries in New Brunswick, 2000 to 2011

Purpose: To estimate the supply of workers in the New Brunswick labour market, particularly the replacement demand, that is, the workers needed to replace those who are no longer employed in the province. The focus will be on three groups: stayers (workers employed in the same industry for one or more years), leavers (workers who leave the labour market or industry) and entrants (workers entering the labour market, including those returning to the workforce).

Description: The annual T1 Family File (T1FF) records of tax-filers who lived in New Brunswick for at least one year from 2000 to 2011 will be selected for this research study. The T1FF records will be linked over this period using Social Insurance Numbers (SIN) to produce a longitudinal analysis file. All direct identifiers, including the SINs, will be removed from the analysis file following completion of the linkage.

The linkage will be produced by Statistics Canada staff on the agency's premises.

Output: Only aggregate statistics and analysis conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Research findings will be used to enhance the labour market policies in New Brunswick. To support on-going analysis, the linked analysis file will be retained at Statistics Canada until April 30, 2016, or sooner if no longer required, at which time it will be destroyed. Access to the linked analysis file will be by Statistics Canada employees or deemed employees whose assigned work activities require such access.

Amendment: Data linkage to examine pathways of Information and Communication Technology (ICT) students through post-secondary education (PSE) and into the labour market, 1998-2011 (057-2013)

Purpose: The main objective of this project is to link the University of Ottawa students administrative data from 1998 to 2011, to the tax data (using the T1 Family File) of the corresponding years. This amendment is to add some aspects of job quality, namely union coverage and pension plan coverage.

The linkage will enable the tracking of post-schooling earning trajectories and acknowledge the presence of some job quality indicators of the jobs of university students in the ICT field of study and also of those with some ICT courses but not in an ICT field of study and compare these with the trajectories of non-ICT students. It will also allow, more generally, to look at student trajectories by various fields of study and to be able to make comparisons between various subgroups.

Description: Records of students from the University of Ottawa will be linked to the T1 Family File (T1FF) over a 14 year period (from 1998 to 2011). The data linkage will be done in two stages:

In the first stage, University of Ottawa will send a file containing the student identification variables as well as a pseudo-identification variable for each student. The linkage will be done with the T1 Family File containing an identification number and a selection of variables to conduct the research. Once the linkage is finalized, the student identification variables will be destroyed except the pseudo-identification variable from the University of Ottawa.

In Stage 2, the University will provide a file with the pseudo-identification variable and the student information. This second file will be linked to the reduced T1FF file from stage 1. The pseudo-identification variable from the University will be destroyed once the linkage is finalized and will not be part of the linked file.

A synthetic file will be created containing the same variables as the linked file but a noise will be introduced into the data. This file will reside at Statistics Canada and will be used by the researchers to plan their tables and models. A Statistics Canada employee will run their programs on the real linked file, apply the vetting rules and transmit the results to the researchers.

The record linkage will be done by Statistics Canada personnel. Individuals' tax data for all available years will be included in the linked file.

Output: Aggregate statistics and analysis conforming to the confidentiality provisions of the Statistics Act will be released to users. The linked file will be retained at Statistics Canada until no longer required, up to, December 31, 2018, after which time it will be destroyed.

The Effectiveness of the Department of Foreign Affairs and International Trade and Development's Trade Commissioner Services (072-2013)

Purpose: This project assesses the effectiveness of the services offered by Department of Foreign Affairs and International Trade and Development's (DFAITD) trade commissioners. The analysis will provide DFAITD with improved information on the economic impact of these services on the export performance, performance and survival of Canadian firms. It will allow DFAITD to determine whether the impacts of the services are consistent with the objectives set out for it by the Government of Canada.

Description: A list of firms in the DFAITD's International Business Development dashboard from 1999 to 2012 will be linked to data from National Accounts Longitudinal Microdata File (data from the Business Register, T2 Corporate tax, PD7, T4, Export Register, Import Register). The firms in the IBD dashboard will be linked probabilistically using name and address and then subjected to a manual review. This is a one-time linkage.

Output: Only non-confidential aggregate statistical outputs and analyses that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada.

The Importance of Governance Structures on Firm Performance in the Portfolio of Firms Receiving Support from the Business Development Bank of Canada (071-2013)

Purpose: This project examines the impact of having a board of directors, an advisory board or both on firm performance. The analysis produced in this project will improve the understanding of whether, when and how certain governance structures improve firm performance, and enable the Business Development Bank of Canada (BDC) to better fulfill its mandate of providing services complementary to those available at other financial institutions with the goal of encouraging the development of small and medium-sized businesses in Canada.

Description: A list of firms in the BDC portfolio in the 2000 to 2010 period will be linked to data from National Accounts Longitudinal Microdata File (data from the Business Register, Corporate tax data-T2 tax database, PD7 and T4). The BDC firms records will be linked probabilistically using name and address. This is a one-time linkage.

Output: Only non-confidential aggregate statistical outputs and analyses that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. The information will be presented in the form of tables of regression results and summary statistics related to the project's goal of ascertaining the impact of having an advisory board or board of directors.

The linked file will be retained until December 2018. All direct business identifiers will be removed from the analysis file once linkage is complete, and placed in a separate linkage key file. The linked file and the linkage key file will be retained until December 2018, or sooner if no longer required, at which time it will be destroyed.

Linking Data from the 2012 Survey of Financial Security to income tax Records file (T1)

Purpose: The purpose of this linkage is to obtain income data and reduce respondent burden, interviewer time and collection costs for the 2012 Survey of Financial Security. The linkage allows obtaining information on income variables without burdening respondents with detailed questions about their income. The income data is important for the Survey of Financial Security and allows analysis of the relationship between income and wealth. This survey is the only Statistics Canada survey that releases information on these topics.

According to the directive on Informing Survey Respondents, the 2012 Survey of Financial Security informs all respondents of this linkage through the inclusion of the statement within the survey collection vehicle and on the STC website. The statement reads:

" In order to reduce the length of the interview, and enhance the information provided in this survey, Statistics Canada will combine this information with information from personal tax data. The information we obtain will be used for statistical purposes only, and will be kept confidential."

Description: The 2012 Survey of Financial Security databaseand the 2011 T1 File will be linked using the address, city, date of birth, first name, surname, sex, province, NYSIIS and SNDX code for surname, postal code, marital status, telephone number and first initial. This information will be removed from the linked file as soon as the linkage is completed, and stored separately. Access to these files will be restricted to Statistics Canada employees whose assigned work activities require access.

Output: No information containing personal identifiers would be released outside of Statistics Canada from this linkage activity. Only aggregate statistics and analysis conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. The Survey of Financial Security is an occasional survey to be conducted from September to November 2012 and therefore, the linkage would be undertaken in 2012/2013.

2011 National Household Survey and Immigrant Landing File linkage

Purpose: A record linkage between the 2011 NHS and the Citizenship and Immigration Canada (CIC) Landing File would permit detailed analysis of socio-economic outcomes of immigrants to Canada by entrance characteristics such as admission category (e.g. refugee, family class, etc.). The results from this record linkage would be used to support and evaluate immigration policies and programs. In addition, the file will be used to strengthen inputs into Statistics Canada's DEMOSIM micro-simulation model.

Description: The National Household Survey (NHS) provides detailed information on the demographic, social and economic characteristics of people in Canada, as well as providing information about the housing units in which they live. The Citizenship and Immigration Canada (CIC) Landing File provides information on immigrants to Canada from 1980–2011 such as admission category and knowledge of official languages at time of landing.

The record linkage between the Landing File and the 2011 National Household Survey was a two-stage process that involved first linking the Landing File to the 2011 Census and then making use of the already existing linkage between the 2011 Census and the 2011 NHS. The record linkage between the Landing File and the 2011 Census employed a hierarchical deterministic record linkage program developed by HSMD for the IMDB. Only NHS respondents will be maintained for this record linkage.

Output: Only aggregate statistical estimates that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Outputs for the Landing File and the NHS linkage will include a wide range of analysis and standard data tables, as well as custom tabulations.

A linkage key will be retained indefinitely as part of this record linkage. The linkage results including variables used to perform the record linkage such as personal identifiers and information used to measure the linkage quality will be destroyed by August 31, 2014. All files will be kept on a server in a secure area. Access to these files is restricted to Statistics Canada employees whose assigned work activities require such access.

2012 Aboriginal Peoples Survey and 2011 National Household Survey Linkage

Purpose: The Aboriginal Peoples Survey (APS) is a national post-censal survey of Aboriginal peoples (First Nations peoples living off reserve, Métis and Inuit) in Canada. The survey provides valuable data on the social and economic conditions of Aboriginal people 6 years of age and over. Data from the APS inform policy and programming activities aimed at improving the well-being of Aboriginal peoples in Canada.

Linking the 2012 APS and the 2011 National Household Survey (NHS), will allow methodologists to derive weights for the APS. As well, an APS-NHS linkage will enrich the analytical potential of the 2012 APS microdata file by allowing data users to analyse APS data with reference to person-level, family-level and household-level information collected in the NHS. NHS data complement the findings of the APS, providing information on topics that were either beyond the scope of the APS or which were explored in the survey in only a very limited way in order to reduce response burden.

Description: Responses to the 2012 Aboriginal Peoples Survey and 2011 National Household Survey will be matched for each respondent using the variables frame_id (which identifies a household uniquely in Canada) and persnr (which identifies a person uniquely within the household). This linkage will result in the APS-NHS linked file. This composite file will be used to create an analytical file which will become the base from which other products will be developed.

Output: Only aggregate statistical estimates that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Linked information from the 2012 Aboriginal Peoples Survey and 2011 NHS will be used in analytical articles and other data products released from the 2012 Aboriginal Peoples Survey. All products containing linked data will be disseminated in accordance with Statistics Canada's policies, guidelines and standards.

The APS analytical file, including linked NHS records, will be created and retained indefinitely by Social and Aboriginal Statistics Division (SASD). The analytical file will not contain any personal identifiers.

2012 Canadian Survey on Disability and 2011 National Household Survey Linkage

Purpose: The Canadian Survey on Disability (CSD) is a post-censual survey which provides information on Canadians whose everyday activities may be limited because of a condition or health-related problem. Information from this survey is essential for the effective development and operation of national programs such as employment equity and is required by the Government of Canada to fulfill various international commitments, including the United Nations Convention on the Rights of Persons with Disabilities.

Linking the 2012 CSD and the 2011 National Household Survey (NHS) is necessary to derive accurate weights for the CSD. As well, a CSD-NHS linkage will enrich the analytical potential of the CSD microdata file by allowing for the analysis of CSD data with reference to person-level, family-level and household-level information collected in the NHS Furthermore, it will allow for the calculation of disability rates and for the comparison of the characteristics of activity-limited CSD respondents with those of non-activity-limited NHS respondents. NHS data complement the findings of the CSD, providing information on topics that were either beyond the scope of the CSD or which were explored in the survey in only a very limited way in order to reduce response burden.

Description: Responses to the 2012 CSD and 2011 NHS will be matched for each respondent using the variables frame_id (which identifies a household uniquely in Canada) and persnr (which identifies a person uniquely within the household). This linkage will result in the CSD-NHS linked analytical microdata file.

Output: Linked data from the 2012 CSD and 2011 NHS will be disseminated on the analytical microdata file produced for the 2012 CSD. All products containing linked data are disseminated in accordance with Statistics Canada's policies, guidelines and standards. Only aggregate statistical estimates that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada.

The linked 2012 CSD-2011 NHS analytical file will be created and retained indefinitely by Social and Aboriginal Statistics Division (SASD). The analytical file will not contain any personal identifiers.

Update: Gross Flows of Workers Into and Out of Industries in Newfoundland and Labrador, 2000 to 2011

Purpose: To estimate the supply of workers in the Newfoundland and Labrador labour market, particularly the replacement demand, that is, the workers needed to replace those who are no longer employed in the province. The focus will be on three groups: stayers (workers employed in the same industry for one or more years), leavers (workers who leave the labour market or industry) and entrants (workers entering the labour market, including those returning to the workforce).

Description: The annual T1 Family File (T1FF) records of tax-filers who lived in Newfoundland and Labrador for at least one year from 2000 to 2011 will be selected for this research study. The T1FF records will be linked over this period using Social Insurance Numbers (SIN) to produce a longitudinal analysis file. All direct identifiers, including the SINs, will be removed from the analysis file following completion of the linkage.

The linkage and specific data requirements will be produced by Statistics Canada staff on the agency's premises.

Output: Only aggregate statistics and analysis conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Research findings will be used by the Government of Newfoundland and Labrador to enhance their labour market policies. To support on-going analysis, the linked analysis file will be retained at Statistics Canada until April 30, 2016, or sooner if no longer required, at which time it will be destroyed. Access to the linked analysis file will be restricted to Statistics Canada employees whose assigned work activities require such access.

Examination of Sentencing Trends for Drug Offences and Motor Vehicle Theft to Revise the Crime Severity Index Weights

Purpose: In order to revise the weights for the Crime Severity Index (CSI), this project links data from the Incident-based Uniform Crime Reporting Survey (UCR2) and the Integrated Criminal Court Survey (ICCS) to examine the hypothesis that court sentencing patterns for drug offences differ according to type of drug involved and that sentencing patterns for motor vehicle theft differs from sentencing patterns for the broader categories of theft. The results of these examinations will be used to inform decisions on appropriate revised weights for these offences in the Index. Conforming to the recommendation to revise the weights every five years, this current project marks the first revision to the Crime Severity Index.

The Crime Severity Index (CSI) is an important addition to existing measures of crime because it measures change in the volume of crime while also taking into account the relative seriousness of crime. The Index relies on courts sentencing data to measure the relative seriousness of crime. Consultations with the justice community have indicated a need to better understand the effects of sentencing practices for offence types.

This record linkage project will contribute to the public good by increasing the confidence of the general public, as well as the police, the academic and justice communities in the measures of crime in Canada. Further, it is in the public interest to better understand if and how the consequences of being convicted of drug offences differs according to the type of drug involved and how the consequences of being convicted of motor vehicle theft differs from the consequences of being convicted of a more general theft.

Description: In order that the weights for the Index can be updated, this linkage will bring together police-reported records from the UCR2 and courts-reported records from the ICCS to allow an analysis of sentencing patterns for drug offences and motor vehicle thefts. ICCS charge records will be linked to UCR2 records using a direct matching methodology of identifiers and linking keys.

Drug offences by specific drug types can only be identified in the police-reported records, so the linkage will allow their identification in courts data. Motor vehicle thefts can only be identified by using incident characteristics data from police-reported records. Prior to November 5, 2010 there was not yet a specific Criminal Code offence for motor vehicle thefts so the linkage will allow their identification in courts data.

Output: A data file will be produced containing court-based charge information with the imputed UCR2 violation code. Results of analysis of this file will be published in a report entitled "Updating the Crime Severity Index Weights: Refinements to the Methodology" (scheduled for release in May 2013). This report is intended to provide information on the methodology behind the revisions made to the weights to be use for the Crime Severity Index for 2012 (including revised 2011 UCR data) to 2016. A discussion of the results of this record linkage will be included. Composite or linked files will be retained until no longer required, up to, April 30, 2018, at which point they will be destroyed, in order for the file to be available for reference next time the CSI weights require updating.

Analysis of the legal components involved in self-identification among First Nations peoples

Purpose: The starting point for this analysis is the mismatch between estimates of the number of Aboriginal people in the Census and in the 2006 Aboriginal Peoples Survey (APS). For Quebec, for example, the APS shows 40% more registered Indians living off reserve than in the Census. This raises the question of how consistently Aboriginal people self-identify. Since most studies on Aboriginal people use either Aboriginal identity or registered Indian status as the variable determining the category, it is clear that if responses to questions are not reliable, the analyses based on them must be verified in light of this information. Guimond (2007) studied this issue by looking at intergenerational and intragenerational mobility, or the tendency for self-reporting to increase over time and in the generations resulting from couples of mixed ancestry. For our part, we are interested in how the reporting for the same individual fluctuates in two separate surveys scarcely a few months apart.

This project is structured around the concept of "fluidity of ethnic identity." It will focus on the components relating to "legal status," i.e., registered Indian status. In the case of Quebec, the project seeks to shed light on the differences between the new identification categories—consistent or inconsistent—and sociodemographic characteristics including education and status. This study will ultimately serve to validate or invalidate various previous studies that did not take fluidity of identity into account.

Description: To perform the planned analyses, access to the 2006 Census-APS linked file, in which the census variables reporting origin, identity and registered Indian status were added to the APS file, is requested. A first series of multivariate descriptive analyses (analysis of matches) will provide an overall picture of the situation. Subsequently, multi-level analyses that take into account the municipality of residence will determine how the consistency of reporting affects variables of interest such as education and income.

Output: Only weighted (rounded) statistics, aggregate analyses and models complying with the confidentiality provisions of the Statistics Act will be disseminated outside Statistics Canada.

Statistics Canada will retain the linked files for five years, until May 15, 2018, or no longer needed, at which time, they will be destroyed.

Atlantic Canada Opportunities Agency (ACOA) - Update of Business Performance Evaluation Report (2010)

Purpose: To assess the effectiveness of ACOA's programs and activities and the usefulness of the Agency's efforts to assist small businesses, and to determine more effective means of providing assistance to the small business community. ACOA assists businesses by providing loans, as well as a broad range of programs and services, for purposes of establishing, expanding, or modernizing businesses, and for the development of human resources. Information resulting from the linkage will be used by ACOA to measure the performance of businesses which received financial assistance under the Agency's programs, and compare it to the performance of other firms in the Atlantic region. Employment dynamics, businesses entering and exiting, selected financial statistics, as well as measures of labour productivity will be analyzed. Findings from this assessment may be used by ACOA to improve assistance to businesses.

Description: A list of ACOA-assisted businesses will be linked to the following files: 2004 to 2010 Business Register, 2010 Longitudinal Employment Analysis Program (LEAP) file, 2004 to 2010 Corporate Tax-General Index of Financial Information (GIFI), 2004 to 2010 Exporter Registry and 2004 to 2010 Research and Development in Canadian Industry database. The files will be linked using the Business Number (BN), Statistical Enterprise Number (SNUM) and the legal/operating name.

Output: Only aggregate statistical outputs and analyses that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. These will be in the form of statistical tables at the business sector and business size level for Atlantic Canada; as well, research and development estimates will be produced at the Canada level. ACOA will publish these results in their annual performance report to Parliament, which will be available on the ACOA website, and in research studies on topics such as entrepreneurial start-ups, employment patterns and growth in Atlantic Canada.

Analyzing the differences in self-identification on the Census and Aboriginal Peoples Survey

Purpose: When we compare the estimates of the number of Aboriginal people living off reserve from the Census and the Aboriginal Peoples Survey (APS), we note a significant difference between the two. This difference is not due to methodology-related issues such as weighting or margin of error. For example, for Quebec, the APS estimates 40 per cent more Aboriginal people living off reserve than the Census. There is only one way to uncover the source of this difference and understand why this is happening: we need to link the two files. We believe that the same individuals provide different information to the two surveys. As a result, an analysis of the factors behind this "inconsistent" reporting is necessary. It is all the more important to understand it because studies on Aboriginal people depend on these responses and consider them "error-free."

Firstly, this study will seek to better understand Aboriginal identification, more specifically the individual characteristics and contexts—province, region, municipality, etc.—that explain the difference in reporting. The findings of this first phase will be used to review the results of analyses that relied on identification criteria from only the Census or the APS to study the situation of Aboriginal people.

Description: For the time being, we would like to have access to a file that provides the identity variables from the census for the same individuals, in addition to APS data. These variables will help us to create new identification variables that take into account the consistency of reporting and to analyze the factors related to this consistency. Initially, an analysis of the matches and classification could provide an overall picture of the groups concerned. Next, standard regression and logistical analyses will be used to identify the variables at the individual level associated with inconsistent reporting. Lastly, multilevel regression methods will help to determine the contexts likely to be linked to inconsistent reporting.

Output: Only aggregate statistics and analyses conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada.

Statistics Canada will retain the linked analysis files for five years, until April 30, 2018 or sooner if no longer required, at which time the said files will be destroyed.

Canadian Employer-Employee Dynamics Database

Purpose: The activities and economic outcomes of workers are shaped in many ways by the firms or organizations in which they are employed, and conversely, worker characteristics have implications for firm performance. Together, individual-level and firm-level data that are integrated to facilitate a more comprehensive understanding of labour market processes and economic outcomes than is possible using either type of data in isolation.

The CEEDD will be a multi-purpose file capable of supporting research on many issues. In addition, a number of priority projects are proposed for 2013-14 and 2014-2015. These include projects on business start-ups and job creation, with particular emphasis on the role of immigrant entrepreneurs; the distribution of immigrants across business enterprises and how this differs from the distribution of Canadian-born workers; how workforce aging is playing out within business enterprises, including its effect on labour productivity; local labour market information, including hiring rates, separation rates, layoff rates, and aggregate turnover rates within sub-provincial regions and the impacts of organizational changes, such as mergers and acquisitions, on individual-level outcomes.

Description: Information at the level of the business-enterprise will be drawn from the National Accounts Longitudinal Micro data File (NALMF) while individual- and job-level data will be drawn from T1 files, the T4 Statement of Remuneration Paid file, the Record of Employment (ROE) file, the Longitudinal Immigration Data Base (IMDB), and the Temporary Foreign Work file, for the years 1999 onward. All linkages will be done on a deterministic basis using Business Numbers (BNs) and/or Social Insurance Numbers (SINs).

Business Numbers and SINs will be transformed into unique personal identifiers that will remain on the business-level and individual-level files in a scrambled form. The use of scrambled identifiers will allow users to differentiate units in the cross-sectional data, and to follow them longitudinally over time. Postal code information will be used to create aggregated geography variables and then removed from the files.

All BNs, SINs and postal codes will be removed from the analytical files and stored in a separate location accessible only to indeterminate Statistics Canada employees who job duties require them to access this information.

Output: The outputs of the proposed database will include two components. One is labour market indicators (e.g. hiring, separations, job creation/destruction) at national, provincial and sub-provincial levels of geography. This information will conform to the confidentiality provisions of the Statistics Act. The other is the longitudinal files that will serve the internal and external researchers. Only aggregate statistics and analysis conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. The linked file and linking key file will be retained by Statistics Canada until no longer required, up to, March 31, 2023, at which time they will be destroyed.

The linked files will be hosted by the Center of Data Development and Economic Research (CDER) of Economic Analysis Division. External researchers will be able to access the linked data on Statistics Canada premises, under the Policy on the Use of Deemed Employees and current MOUs with the CDER. Synthetic files will be created for external researchers for direct access, while the original files will only be accessed via batch mode with no viewing function. Research studies will be published in Statistics Canada's Research Paper Series as well as in academic journals. Research studies will also be presented at professional conferences.

Long Term Income and Employment Among Breast Cancer Survivors: Linkage of British Columbia Breast Cancer Data and the Longitudinal Administrative Databank

Purpose: The goal of this study is to provide information on income and employment of breast cancer survivors that will inform the development of strategies and supports to facilitate return to work, reduce financial hardship, and improve the long-term financial circumstances of breast cancer survivors, from diagnosis to end of life.

Description: The client proposes to use a linked database consisting of cancer registry clinical databases from the British Columbia Cancer Agency, and Statistics Canada's Longitudinal Administrative Databank (LAD) 1982 to 2010, to directly measure long-term burden and change in income and employment, and determinants of income, employment, and change over time and stage in the cancer trajectory, among those with breast cancer in British Columbia. Only indeterminate authorized Statistics Canada personnel will perform the linkage. Following completion of the linkage, all personal identifiers will then be removed from the linked file. No names or addresses will be on the final linked analysis data file. Detailed data analysis of this final linked file will be undertaken by Statistics Canada personnel and/or deemed Statistics Canada employees under the strict provisions of the Statistics Act.

Output: Only aggregate data and analysis conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Findings will be disseminated in a variety of professional and academic venues including research papers as well as presentations to Canadian academic conferences. Depending on requests, there may be wider dissemination of the research results. The linked file and identifiers will be retained separately at Statistics Canada only until 31 March, 2018, or sooner, after which time they will be destroyed.

Amendment to Canada Student Loans Program Linkage to the Longitudinal Administrative Databank (CSLP-LAD)

Purpose: On August 1, 2000, a direct loan regime was adopted for Canada Student Loans in which the Government of Canada issues loans directly to students and receives the repayments of those loans. The purpose of the original linkage (011-05) was to assess the effectiveness of this new regime in reducing loan repayment difficulties. This request is for an extension to the date of retention of the linkage, between Canada Student Loan Program (CSLP) data and the Longitudinal Administrative Databank (LAD), from February 2013 to March 31, 2016.

Description: LAD data files for the years 1985 to 2003 are linked to administrative records from the Canada Student Loan Program (CSLP) for the years 1991 to 2000. The LAD data prior to 1991 (the beginning of the CSLP data) are to be included because it provides information about the socio-economic and demographic situation of students prior to, and during their PSE years, through variables such as parental income, parental urban/rural residency, parental provincial residency and student's employment during PSE study. All direct identifiers, including the SINs, will be removed from the analysis file following completion of the linkage.

The linkage and specific data requirements will be produced by Statistics Canada staff on the agency's premises.

Output: Only aggregate statistics and analysis conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Research findings will be used by Student Loans Program, Human Resources and Skills Development to enhance student loan policies. To support on-going analysis, the linked analysis file will be retained at Statistics Canada until March 31, 2016, or sooner if no longer required, at which time it will be destroyed. Access to the linked analysis file will be restricted to Statistics Canada employees whose assigned work activities require such access.

Expanding the Longitudinal Analytical Databank (LAD) to include Tax Free Savings Account (TFSA) information

Purpose: The debut of the Tax Free Savings Account (TFSA) in 2009, introduced a new program that is separate from and is not captured by the T1 tax file, upon which the Longitudinal Analytical Databank (LAD) is based. The TFSA program may have an effect on the measurement of income, particularly when focusing on the retired population, as well as more generally on the tax and transfer system. The proposed addition of TFSA information to the LAD will permit Statistics Canada to improve its data reporting on income and wealth, and thereby assist our clients with their research in this area.

Description: The project involves linking on a continuing basis Statistics Canada's LAD file to the TFSA file from Canada Revenue Agency (CRA). The LAD and TFSA will be linked deterministically using the Social Insurance Number (SIN) of individuals. Following completion of the linkage, the SIN and other identifiers will then be removed and kept securely separate from the final linked file. No names or addresses will be used at any point in the linkage process or be on any of the files used. The linkage will be performed by Statistics Canada personnel.

Output: The output will be a linked database file combining LAD and TFSA information. Only aggregate data and analysis conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. The linked file will be retained at Statistics Canada.

Update: Gross Flows of Workers Into and Out of Industries in Newfoundland and Labrador, 2000 to 2010

Purpose: To estimate the supply of workers in the Newfoundland and Labrador labour market, particularly the replacement demand, that is, the workers needed to replace those who are no longer employed in the province. The focus will be on three groups: stayers (workers employed in the same industry for one or more years), leavers (workers who leave the labour market or industry) and entrants (workers entering the labour market, including those returning to the workforce).

Description: The annual T1 Family File (T1FF) records of tax-filers who lived in Newfoundland and Labrador for at least one year from 2000 to 2010 will be selected for this research study. The T1FF records will be linked over this period using Social Insurance Numbers (SIN) to produce a longitudinal analysis file. All direct identifiers, including the SINs, will be removed from the analysis file following completion of the linkage.

The linkage and specific data requirements will be produced by Statistics Canada staff on the agency's premises.

Output: Only aggregate statistics and analysis conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Research findings will be used by the Government of Newfoundland and Labrador to enhance their labour market policies. To support on-going analysis, the linked analysis file will be retained at Statistics Canada until April 30, 2015, or sooner if no longer required, at which time it will be destroyed. Access to the linked analysis file will be restricted to Statistics Canada employees whose assigned work activities require such access.

Economic Development Agency of Canada for the Regions of Quebec (EDAC): Economic Impact – 2001 to 2010

Purpose: To support the evaluation of the Economic Development Agency of Canada for the Regions of Quebec's (EDAC) financing services program, by producing objective measures of its economic impact on the performance of small and medium-sized enterprises (SMEs). Key performance indicators, and value-added measures such as sales, profits, firm survival rate, and employment, will be calculated for EDAC client businesses and for comparable non-client businesses.

Description: A list of firms that were EDAC clients in the period 2001 to 2010 will be linked to the Business Register to obtain the Business Number and Statistical Enterprise Number, to facilitate linkage to payroll and tax data. In order to measure the effectiveness and the impact of EDAC financing services, a comparison group of non-EDAC client firms with similar characteristics will be selected.

Records of EDAC clients and the businesses in the comparison group will be linked to the Payroll Deduction Account (PD7), the T1 Unincorporated Business Tax Data, the T2 Corporate Tax data, the General Index of Financial Information (GIFI), Exporter Registry and Research and Development in Canadian Industry (RDCI) for the period 2001 to 2010. The records will be linked using the Business Number and Statistical Enterprise Number. The resulting linked analysis file will enable longitudinal analysis of each cohort. This is a one-time linkage.

Output: Only non-confidential aggregate statistical outputs and analysis that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. These will be in the form of separate summary tables of regression analysis results relating to the study hypotheses of the economic impact of EDAC's financing services, in addition to profiling tables. A methodology report will be prepared, explaining the file matching processes and constraints and key issues related to the quality of the data. An analytic report will be produced by Statistics Canada.

Linkage of Survey of Intellectual Property Management (SIPM) 2010 to the Linkable File Environment (LFE)

Purpose: The purpose of this record linkage is provide Industry Canada researchers and other researchers the opportunity to carry out policy relevant research using the data in the SIPM 2010 and the data available in other databases that are in the LFE.

Description: This is a request to link the Survey of Intellectual Property Management (SIPM) 2010 to the Linkable File Environment (LFE).

Output: The linkable SIPM dataset will be housed at Statistics Canada's Centre for Special Business Project (CSBP). When a research project is formally approved by Statistics Canada, Statistics Canada's Centre for Special Business Projects will extract a researcher database from the LFE which will contain data for the variables that are listed in the research proposal for the population that has been specified. Access to the researcher database will be facilitated and managed by Statistics Canada's Centre for Data Development and Economic Research (CDER).

• Extension of retention period; 2013 General Social Survey on Giving, Volunteering and Participating: linking tax data from the T1 Personal File, T1 Family File and T4 Summary and Supplementary file. (047-2014)
• Amendment for an extension of the Retention Period for BC Venture Capital Data, Industry Canada: The Impact of Angel Investment on Company Performance (054-2014)
• Longitudinal and International Study of Adults: Linkage to the Longitudinal Immigrant Database Landing File component (077-2014)
• Atlantic Canada Opportunities Agency (ACOA) – Update of Business Performance Evaluation Report (2015): (082-2014)
• Community Futures Program’s (CF) Regional Economic Contribution: Linkage of Client List to Business Tax and Employment Data, 2007 to 2012 (083-2014)
• Linkage of the 2013 General Social Survey (GSS) Cycle 27, Social Identity, and the Longitudinal Immigrant Database (090-2014)
• Examination of Sentencing Trends for Drug Offences (093-2014)
• Linkage of the Census of Population 2006 to the Discharge Abstract Database, the Canadian Mortality Database and the Landing File for Purposes of the Longitudinal Health and Administrative Data (LHAD) Initiative (088-2014)
• Canadian Forces Mental Health Survey (CFMHS) – 2013: Linkage to obtain information on Canadian Forces members' deployment history and medication use (055-2013)
• Census of Agriculture Linkage to Taxation Data (064-2014)
• Creation of a Derived Record Depository and Key Registry for the Purposes of the Social Data Linkage Environment (085-2014)
• Longitudinal Apprentices and Trades Qualifiers Database (065-2014)
• Longitudinal and International Study of Adults: Business Register Linkage (044-2014)
• Re-contact with the Saskatchewan justice system (052-2014)
• Business Performance Measurement of Various Programs for the Evaluation Directorate of the Federal Economic Development Agency for Southern Ontario (FedDev Ontario) – 2006 to 2013 (053-2014)
• Linkage to the Canadian Mortality Database for the purposes of the PeriOperative Ischemic Evaluation (POISE Trial) Study (031-2014)
• The financial characteristics of Refugee Claimants in Canada (007-2014)
• Linkage of the Industry Canada Database of Canadian Patents Filed in the United States Patent and Trademark Office (USPTO) 2000-2011 to the Linkable File Environment (LFE) (015-2014)
• Use of linkages between the 2001 and 2006 censuses and between the 2006 Census and the 2011 NHS/Census for analyses and projections of different population groups (006-2014)

Extension of retention period; 2013 General Social Survey on Giving, Volunteering and Participating: linking tax data from the T1 Personal File, T1 Family File and T4 Summary and Supplementary file. (047-2014)

Purpose: This amendment to the previously approved record linkage 045-2013. There is no change to the proposal other than the extension of the retention period.

The General Social Survey (GSS) program, established in 1985, conducts telephone surveys from a sample selected across the 10 provinces (excluding the Territories). The GSS is recognized for its regular collection of cross-sectional data that allows for trend analysis, and its capacity to test and develop new concepts that address emerging issues. Each year the GSS focuses on a different topic, such as family, victimization, social support and aging, and time use. A specific topic is usually repeated approximately every 5 years. The 2013 GSS will focus on Giving, Volunteering and Participating (GVP).

The 2013 GSS on GVP is the fifth iteration of a series of surveys that began with the 1997 National Survey of Giving, Volunteering and Participating (NSGVP). This survey is the result of a unique partnership of federal government departments and non-profit and voluntary organizations that includes Imagine Canada, Canadian Heritage, Health Canada, Human Resources and Skills Development Canada, the Public Health Agency of Canada, Statistics Canada and Volunteer Canada.

Previous iterations were overseen by the Special Surveys Division. The survey is now developed and conducted by the Social and Aboriginal Statistics Division. This survey is an important source of information on Canadian contributory behaviour, including giving, volunteering and participating.

By linking the 2013 GSS on GVP responses to personal tax files of respondents, and the tax files of all household members, more accurate income (personal and household), and claimed tax credits for charitable donations information will be obtained for respondents. At the same time, response burden will be minimized, and collection, data processing, and testing costs will be reduced.

Description: The 2013 GSS on GVP is a sample based survey with a cross-sectional design. Telephone surveys are conducted through computer assisted telephone interviews from a sample selected across the 10 Canadian provinces.

By linking data, we are aiming to obtain better quality data for income (personal and household) and tax credit information claimed for charitable donations.

Questions relating to income show rather high non-response rates, the incomes reported by respondents are usually rough estimates and donor imputation is used for partial and item non-response.

Since respondents do not always complete their own tax reports, it can be difficult for them to remember if they claimed a tax credit in their most recent tax report. Linking will allow getting such information without having to ask questions.

The information collected during the 2013 GSS on GVP will be linked to the personal tax records (T1, T1FF or T4) of respondents, and tax records of all household members.

Respondents will be notified of the planned linkage before and during the survey. Any respondents who object to the linkage of their data will have their objections recorded, and no linkage to their tax data will take place.

Output: The availability of the 2013 GSS on GVP analytical data file will be announced in The Daily. The analysis file will be made available to Statistics Canada researchers, and to deemed employees at the Statistics Canada Research Data Centres. All data will remain confidential and protected under the Statistics Act.

Along with the availability announcement of the analytical data file (in The Daily), only non-confidential aggregate statistics will be released.

Amendment for an extension of the Retention Period for BC Venture Capital Data, Industry Canada: The Impact of Angel Investment on Company Performance (054-2014)

Purpose: This project investigates the association between venture capital and angel investments (individuals that invest their own money in other people's businesses) and business performance in order to inform federal and provincial policy.

Description: This project investigates the extent to which risk capital investment is associated with improved business performance. The sample of risk-capital backed companies comes from three sources: (1) companies that have received investment as part of British Columbia's Venture Capital Program, which provides tax credits to encourage the investment of risk capital in small businesses; (2) National Angel Capital Organization Surveys of Angel Group Investments; and (3) venture-capital backed companies identified by Thomson One. These data are linked to financial and employment information maintained at Statistics Canada, and a database that identifies companies supported by the Industrial Research Assistance Program, to assess the performance of these risk capital back companies relative to the general firm population.

Output: Only non-confidential aggregate statistical outputs and analyses that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. The information will be presented in the form of separate summary tables of regression analysis results relating to the impact of venture capital and angel investment on company performance, in addition to profiling tables.

Records from the BC Venture Capital Program and associated linkage keys will be destroyed on March 31, 2016. The linked analysis file, without the BC Venture Capital Program data, will be retained until no longer required, up to, November 15, 2021, at which time it will be destroyed. All direct business identifiers will be removed from the analysis file once linkage is complete, and placed in a separate linkage key file. The linkage key file, without the linkage keys for BC Venture Capital Program, will be retained until at least November 15, 2021 at which time it will be destroyed.

Longitudinal and International Study of Adults: Linkage to the Longitudinal Immigrant Database Landing File component (077-2014)

Purpose: To improve the quality of the data collected for the survey and to reduce response burden and survey costs.

The LISA is a voluntary, multi-topic, longitudinal, socioeconomic survey of households. The survey was designed to meet the key policy data needs of Employment and Social Development Canada (ESDC) in the domains of education and training, family health, income and employment. The results will inform all levels of government as they develop services to better meet the challenges of Canada's society and economy in the 21st century. Researchers, educators, learning institutions and organizations will also use the results of the survey to develop more-effective policies, services and programs for the people most in need.

By linking the LISA respondents to the IMDB Landing File component, data from the time of immigration will be obtained for immigrant respondents. At the same time, response burden and respondent fatigue will be minimized. The linkage will add data which complements the education, family, work and income information collected.

Description: LISA includes every member of a selected household. The information collected on the LISA survey will be linked to each household member's IMDB Landing information when it exists. The data will be linked for the duration of the LISA survey (which has no pre-determined number of collection waves), or until the respondent is no longer participating in the survey.

Respondents to LISA are currently informed of potential for future linkages. Any respondents who object to the linkage will have their objection recorded and no linkage to the IMDB will take place.

Output: The linked file, with all personal identifiers removed, will be maintained, stored and retained in a secure location by ISD. This file will be retained indefinitely. A separate linking key file containing personal identifiers used in the administrative file linkage will be held in a different, secure location, and retained until the completion of processing of the final wave of the survey, after which it will be destroyed.

All information released outside of Statistics Canada will conform to the confidentiality provisions of the Statistics Act.

Atlantic Canada Opportunities Agency (ACOA) – Update of Business Performance Evaluation Report (2015): (082-2014)

Purpose: To assess the effectiveness of ACOA's programs and activities and the usefulness of the Agency's efforts to assist small and medium-sized enterprises, and to determine more effective means of providing assistance to this business community. ACOA assists businesses by providing loans, as well as a broad range of programs and services, for purposes of establishing, expanding, or modernizing businesses, and for the development of human resources. Information resulting from the linkage will be used by ACOA to measure the performance of businesses which received financial assistance under the Agency's programs, and compare it to the performance of other firms in the Atlantic region. Employment dynamics, businesses entering and exiting, selected financial statistics, as well as measures of labour productivity will be analyzed. Findings from this assessment may be used by ACOA to improve assistance to businesses.

Description: A list of ACOA-assisted businesses will be linked to the following files: 2002 to 2012 Business Register, 2012 vintage Longitudinal Employment Analysis Program (LEAP) file, 2002 to 2012 Corporate Tax-General Index of Financial Information (GIFI), and 2002 to 2012 Research and Development in Canadian Industry database. The files will be linked using the Business Number (BN), Statistical Enterprise Number (SNUM) and the legal/operating name.

Output: Only non-confidential aggregate statistical outputs and analysis that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. These will be in the form of statistical tables at the business sector and business size level for Atlantic Canada; as well, research and development estimates will be produced at the Canada level. ACOA will publish these results in their annual performance report to Parliament, which will be available on the ACOA website, and in research studies on topics such as entrepreneurial start-ups, employment patterns and growth in Atlantic Canada.

Community Futures Program's (CF) Regional Economic Contribution: Linkage of Client List to Business Tax and Employment Data, 2007 to 2012 (083-2014)

Purpose: To provide statistical information to support the assessment of the effectiveness of the Community Futures Program in assisting small- and medium-sized enterprises, by comparing the performance of enterprises that received financial assistance under the program to the performance of other unassisted enterprises in the same region. This information will be used by the regional development agencies (RDAs) which manage the CF programs to determine more effective means of providing assistance to their clients. Employment dynamics, enterprises entering and exiting, selected financial statistics, as well as measures of employment will be analyzed. Findings from this evaluation may be used by the regional agencies to improve assistance to enterprises.

Description: A list and updated lists of enterprises assisted by the Community Futures Program will be linked to the following files: 2007 to 2012 Business Register; 2007 to 2012 vintage Longitudinal Employment Analysis Program database (LEAP); and reference years 2007 to 2012 of the General Index of Financial Information (GIFI). Unassisted enterprises will also be linked to these files to provide comparative data.

Output: The outputs released outside of Statistics Canada will be non-confidential aggregate statistics and analyses that conform to the confidentiality provisions of the Statistics Act. The information will be presented in the form of statistical tables, broken down by RDA region, industry sector and enterprise size.

The linked analysis file, containing the linkage keys and identifiers, will be retained until March 31, 2019, or until no longer required, at which time it will be destroyed.

Linkage of the 2013 General Social Survey (GSS) Cycle 27, Social Identity, and the Longitudinal Immigrant Database (090-2014)

Purpose: A record linkage between the 2013 General Social Survey (GSS) on Social Identity and the Citizenship and Immigration Canada (CIC) Longitudinal Immigrant Database (IMDB) would permit analysis of social outcomes (such as civic participation) of immigrants to Canada by entrance characteristics such as admission category (e.g. refugee, family class, etc.). The results from this record linkage would be used by Citizenship and Immigration Canada to support and evaluate immigrant policies and programs.

Description: The General Social Survey (GSS) on Social Identity provides detailed information on the social and civic integration of immigrants and ethno-cultural minorities into Canadian society. The Longitudinal Immigrant Database (IMDB) provides information on immigrants to Canada from 1980–2012 such as admission category and Low Income Measures.

The record linkage between the Landing File and the 2013 General Social Survey employed a hierarchical deterministic record linkage program developed by HSMD for the IMDB.

Only GSS respondents will be maintained for this record linkage.

Output: Only non-confidential aggregate statistical estimates that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Outputs for the Longitudinal Immigrant Database (IMDB) and the General Social Survey (GSS) on Social Identity linkage will include a collection of cross-tabulations between these two sources.

The linkage results including variables used to perform the record linkage such as personal identifiers and information used to measure the linkage quality will be destroyed by March 31, 2016 (or sooner if no longer required). All files will be kept on a server in a secure area. Access to these files is restricted to Statistics Canada employees and deemed employees of Statistics Canada whose assigned work activities require such access.

Examination of Sentencing Trends for Drug Offences (093-2014)

Purpose: The objective of this project is to link records from the UCR2 Survey and the ICCS to examine court case processing and outcomes for drug-related crime. This linkage will allow us to match police-reported incident records, including type of substance, with the corresponding charge records from the courts data. The reference period used for this linkage will be from 2008/2009 to 2011/12 for the ICCS and 2007 through 2012 for the UCR.

This record linkage project will contribute to the public good by increasing the confidence of the general public, as well as the police, the academic and justice communities in the measures of crime in Canada. Further, it is in the public interest to better understand if and how the consequences of being convicted of drug offences differs according to the type of drug involved.

Description: The Canadian Centre for Justice Statistics is undertaking a project on drug-related offences in Canada, including the processing of drug offences by the courts.

The study will look at the outcome of drug-related charges laid by police services and processed in Canada's criminal courts. The information examined includes the decisions handed down by the courts; the average processing time (from the appearance to the conviction); the type and length of sentences imposed; and the aggravating or mitigating factors considered in determining the sentence (type of substance, type of offence, type of plea, age of offender, etc.).

As drug offences by specific drug types can at present only be identified through police-reported records, the proposed linkage will allow their identification in courts data.

Output: A data file will be produced containing court-based charge information with the imputed UCR2 violation code. Results of analysis of this file will be published in a Juristat Article (and accompanying article in The Daily) entitled Drug-related crime in Canada (scheduled for release in 1st quarter 2015). This report is intended to provide information on sentencing trends and patterns for drug-related offences by specific type of drug. A discussion of the results of this record linkage, including relevant methodology and record linkage considerations, will be included. Composite or linked files will be retained until no longer required, up to, March 31st, 2020, at which point they will be destroyed, in order for the file to be available for reference the next time a Juristat article examining trends in drug-related offences is published.

Linkage of the Census of Population 2006 to the Discharge Abstract Database, the Canadian Mortality Database and the Landing File for Purposes of the Longitudinal Health and Administrative Data (LHAD) Initiative (088-2014)

Purpose: To meet the requirements of the LHAD Initiative Research Agenda, the Census of Population 2006 (2a and 2b) will be linked to the Discharge Abstract Database (DAD), the Canadian Mortality Database (CMDB) and the Landing File (LF) to investigate the hospitalization patterns among: 1) Aboriginal groups; 2) immigrant groups; and 3) older adults. As well, there will be an assessment of the validity of the linked file for use in health services research.

As hospitals comprise the single largest share of all healthcare expenditures and costs continue to rise, understanding their patterns of use is critical. In particular, better understanding of the patterns of use among key sub-groups such as Aboriginal peoples and immigrants, who otherwise cannot be identified in administrative data, could assist policy makers in identifying groups at high risk for hospitalizations including those risks that are potentially modifiable via adaptive health services, public promotion, and prevention strategies.

Furthermore, given the richness of the Census data, the data will provide a first ever look at the potential differences in use among Aboriginal groups living on and not on reserve. This is critical information for health care planners, including those at the Federal level, responsible for the delivery of services to these communities.

Similarly, the linked data will provide a unique opportunity to investigate the critical differences of health services use patterns by country and region of birth, time since immigration, generational status and admission category (e.g. refugees). Policy makers require information on the utilization patterns of immigrants by all dimensions to inform their decision making.

Finally, better understanding the socio-demographic characteristics of older adults being hospitalized in acute care facilities, over and above the clinical factors related to their hospitalization, could inform policy makers on the need for more adaptive services outside of hospitals and inform healthcare planners on the potential resource load based on the demographic characteristics of the population they serve.

Description: The Census of Population 2006 (2a and 2b) will be linked to the Discharge Abstract Database (DAD), 2004/2005 to 2009/2010, the Canadian Mortality Database (CMDB), 2006 to 2010 and to the Landing File, 1980 to 2011.

The linked Census/DAD/CMDB/LF file will contain only those data items required to conduct the studies. All direct personal identifiers and addresses are removed from the analysis file. Personal identifiers used for linkage purposes, such as name, death registration number and health insurance number, are stored in separate files.

Output: The linked Census/DAD/CMDB/LF file will remain within Statistics Canada. All access to the linked microdata file will be restricted to Statistics Canada staff whose work activities require access. Only aggregate data that conform to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Research papers based on analyses of the linked data will be submitted for publication in the Statistics Canada peer-reviewed quarterly, Health Reports, as well as in medical or epidemiological journals or released as a working paper in the Health Research Working Paper Series.

The linked analysis file will be retained until December 31, 2018, or until no longer required by Statistics Canada, at which point the continued retention of the file will be reviewed.

Canadian Forces Mental Health Survey (CFMHS) – 2013: Linkage to obtain information on Canadian Forces members' deployment history and medication use (055-2013)

Purpose: The CFMHS is a voluntary survey undertaken on behalf of the Department of National Defence (DND) of both regular members of the Canadian Forces and Reservists who have previously been deployed in support of Canada's mission in Afghanistan. Data collection began April 15^th, 2013 and concluded August 30^th, 2013. The survey was designed to meet the key policy data needs of the Directorate of Mental Health outlined by the Canadian Forces Health Services Group at DND.

The objectives of this survey are:

• To assess the mental health status and functioning of CF members on both illness and positive mental health continuums through selected mental disorders, mental health problems, and well-being;
• To assess timely, adequate, and appropriate access to and utilization of formal and informal mental health services and supports as well as perceived needs;
• To evaluate changes in patterns of mental health and service use;
• To evaluate the mental health impact of the CF work environment and deployments.

The objective of the linkage is to enhance response information from the Canadian Forces Mental Health Survey (CFMHS) with additional information provided by the Department of National Defence (DND) on deployment history and medication use contained in administrative files. By linking CFMHS responses to administrative records, the accuracy of deployment records and drug identification numbers will be high.

Description: This project involves two key record linkages. The proposed record linkage activities would permit the study on the effects of deployment on mental health as well as medication use. The linkages would consist of:

• CFMHS Master file linked to Canadian Forces members' deployment history.
  These administrative data have been compiled by DND using their Central Computerized Pay System (CCPS) data and Canadian Forces Planning, Tasks and Operations (CFPO) system data. The CCPS data would only be used to determine length of deployment history. No income/wage data would be made available. The CFPO data would be used to determine if and where a deployment took place. If a deployment occurred, the month and year of departure as well as the total number of days deployed for each deployment will be linked.

• CFMHS Master file linked to Canadian Forces Pharmacy System.
  This would be done using medication use data supplied by DND. Data would be grouped using a classification of medications previously approved for the 2012 Mental Health component of the Canadian Community Health Survey (CCHS). For each of 17 medication groups, DND would provide an indicator of usage as follows: 0 = No use of the medication for the past 12 months (prior to interview date); 1 = Usage in the past 12 months but no current use; 2 = Current use.

Output: The output of the linkage will be a linked analysis file containing all of the CFMHS variables, as well as the above noted deployment and medication information. Only non-confidential aggregate statistics and analyses conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada.

The availability of the linked CFMHS file will be announced in The Daily and made available to researchers at Statistics Canada's Research Data Centres.

Census of Agriculture Linkage to Taxation Data (064-2014)

Purpose: The Census of Agriculture and taxation data linkage will provide additional information to validate (and impute if necessary) total farm revenues and expenses, and to improve data quality of data in other parts of the questionnaire. Another application of the taxation data will be to identify new farms (“births” units) that had filed a tax declaration with Canada Revenue Agency but were not yet present on the most up-to-date version of the Business Register prior to Census of Agriculture day.

The proposed linkage builds on the feasibility study undertaken for the linkage the of 2011 Census of Agriculture and taxation data. The feasibility study showed that by using taxation data in place of farmers' responses to the Census of Agriculture questionnaire in production, Statistics Canada would be able to significantly reduce their response burden.

Description: Statistics Canada will link farm business taxation data from the Statement of Farming Activities of T1 and T3 taxfilers and the income statement and balance sheet information for T2 filers, as well as the T4 Summary report, to the Censuses of Agriculture, starting with the 2014 Census of Agriculture Test.

Output: Linkage results of the 2016 Census of Agriculture may be disseminated. The linkage will be use to validate total farm revenue and expenses, other content associated with these expense variables, and to identify new farms.

Upon project approval from the Treasury Board Secretariat, a new record linkage application for 2021 and beyond will seek approval to disseminate detailed farm operating expenses, delivering high-quality taxation replacement data.

Statistics Canada will retain the Census of Agriculture years and the Census of Agriculture Test years linked analysis files until no longer required, up to 3 years after linkage, at which time they will be destroyed.

Creation of a Derived Record Depository and Key Registry for the Purposes of the Social Data Linkage Environment (085-2014)

Purpose: The Social Data Linkage Environment (SDLE) builds on past record linkage experience to make possible a program of pan-Canadian socio-economic record linkage research. A well structured and regulated program of record linkage will increase the relevance of existing Statistics Canada surveys; substantially increase the use of administrative data; facilitate the integration of data from various social domains, such as health, education, justice and income thereby increasing the ability to analyse the impact of social determinants from any of these domains to the outcomes in other domains; reduce the burden on survey respondents by re-using already collected data; and maintain the highest data privacy and security standards.

A Derived Record Depository (DRD) and separate Key Registry will be created to reduce privacy risks and to improve the efficiency and quality of the linkages.

Statistics Canada has responsibility for securely storing and processing data files and for the production of analysis files needed to carry out approved research studies. SDLE research projects will involve the use of linked records, and in accordance with Statistics Canada's Directive on Record Linkage, approval by the Chief Statistician is required for each new linkage project.

Description: The DRD is created by linking various Statistics Canada data files for the purpose of producing a list of unique individuals. Each individual in the DRD is assigned an anonymous SDLE identifier. The identifier is randomly assigned and has no value outside of the SDLE. Some of the data files used for the DRD include the Census of Population and National Household Survey, T1 Personal Master Files (Tax), Canadian Child Tax Benefits files, Vital Statistics - Birth Database, Vital Statistics – Death Database, the Landed Immigrant File and the Indian Registry. Future updates to these files will be used for further updates to the DRD.

The DRD would initially be comprised of the following personal identifiers: Surnames; Given names; Date of birth; Sex; Marital status; Date of landing/immigration; Date of emigration; Date of death; Social Insurance Numbers (SIN), Temporary Taxation Numbers (TTN), Dependant Identification Numbers (DIN); Spouse's SIN/TTN; Dependant/Disabled individual SIN/TTN/DIN; Parent SIN/TTN; Health Information Numbers; Addresses; Address Registry Unique Identifier; Standard Geography Classification codes; Telephone numbers; Spouses' surname; Mother's surname; Father's surname; Alternate surname and a Statistics Canada generated sequential identification number for each individual identified through the annual DRD linkage process. Access to the DRD will be restricted to the Statistics Canada employees responsible for its development and maintenance.

Linkage of the DRD to administrative and survey databases held by Statistics Canada will be performed in a dedicated social domain record linkage environment (the “SDLE”). To ensure a high level of data security and privacy, the association of Statistics Canada-generated identification numbers from the DRD and the administrative and survey database Record Identifiers will be stored in a separate Key Registry, thus avoiding the need to store survey data with personal identifiers. For analytical studies, the associated SDLE Identifiers and the Record Identifiers will be used to link an individual's records within and among the databases in the SDLE. All such analytical studies will require prior linkage approval from Statistics Canada's Executive Management Board. Access to the Key Registry will be restricted to the Statistics Canada employees responsible for its development and maintenance and those responsible for the creation of linked analysis data files.

The Key Registry will contain linkage keys to permit linkage for approved studies to data files held at Statistics Canada. Some of these files include but are not limited to:

• T1 Personal Master Files;
• Canadian Child Tax Benefits files;
• Longitudinal Immigration Database;
• Vital Statistics - birth and death databases;
• Sample portion of Census of Population (1991 onward);
• National Household Survey (2011 onward);
• National Longitudinal Survey of Children and Youth;
• Longitudinal Survey of Immigrants to Canada;
• Survey of Labour and Income Dynamics;
• Youth in Transition Survey;
• National Population Health Survey;
• T1 Family File;
• Clinical administrative databases (inpatient and outpatient hospital records, 1992 onward);
• Canadian Cancer Registry;
• Canadian Community Health Survey (all cycles);
• Canadian Health Measures Survey (all cycles).

Output: No information from the DRD will be released outside of Statistics Canada. The DRD and Key Registry will be used exclusively to support the development of research files within the SDLE. Statistics Canada will retain the DRD and Key Registry files until it is determined that there is no further need for them.

Research projects will be approved on a study-by-study basis. These may be carried out as part of a research agenda initiated by Statistics Canada or in response to client requests. A summary of each approved study will be posted on the Statistics Canada web site.

Longitudinal Apprentices and Trades Qualifiers Database (065-2014)

Purpose: This initiative will create a set of linkable data files containing information on individuals enrolled in apprenticeship programs in Canada since 2002. The linkable data files will be used to examine issues pertaining to the completion of apprenticeship programs and the mobility and outcomes of apprentices and trades qualifiers.

Description: The sample for the linkage data files is comprised of individuals who were enrolled in apprenticeship programs, including trades qualifiers. Socio-demographic information on individuals, the apprenticeship program in which they are registered, and their status in the program, will be drawn from the Registered Apprenticeship Information System (RAIS) for the years from 2002 onward. This information will be linked to various administrative data bases. Specifically, job-level information will be drawn from the T4 file, individual-level information from the T1 Family File, T1 Personal Master File, T1 Historical File, T4E file, Employment Insurance Status Vector file, Record of Employment file, and Longitudinal Immigration Data file, and firm-level information from the Longitudinal Employment Analysis Program.

Business Numbers and SINs will be transformed into unique identifiers that will remain on the linkable files to facilitate longitudinal analyses. All Business Numbers (BNs), Social Insurance Numbers (SINs) and personal identifiers will be removed from the analytical files and stored in a separate location accessible only to Statistics Canada employees whose job duties require them to access this information.

Output: Methodological and analytical findings resulting from these linked data will be used to prepare research papers for publication in analytical reports, peer-reviewed scientific journals, CANSIM, for presentation at conferences, workshops and meetings.

Only aggregate statistics and analysis conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada.

Longitudinal and International Study of Adults: Business Register Linkage (044-2014)

Purpose: To improve the quality of the data collected for the survey and to reduce response burden and survey costs.

The Longitudinal and International Study of Adults (LISA) currently captures North-American Industrial Coding Sytem (NAICS) code for the primary employer of respondents who are currently employed, and for the most recent employer of respondents who are not currently employed.

The linkage of NAICS codes from the Business Register to LISA T4 data would improve the amount of data available on a respondent's industry of work when compared to their T4 information, as it would provide NAICS codes for all employers, rather than just the most recent employer.

The linkages will add retrospective data on industry of employment for all paid work for which respondents receive a T4, which complements retrospective education, family and work already collected in the survey.

Description: Data linkages will be made for all respondents (excluding those who object to the linkage statement). Business Number (BN), the legal name of the business, a flag indicating if the business has multiple operations/locations/provinces, the province(s) of operation, NAICS code(s), and the legal code (indicating the primary industry of the business) for all employers will be retrieved from the Business Register file.

A linkage will be made to T4 data for each collection year of the survey, and all previous calendar years going back to 2000. Only Statistics Canada employees directly involved in data processing in Income Statistics Division (ISD) will have access to the annual files and the linking key file containing personal identifiers.

Output: The linked file will be outputted as a microdata file (all personal and business identifiers will be removed) and will be maintained, stored and retained in a secure location by ISD. This file will be retained indefinitely. A separate linking key file containing personal and business identifiers used in the administrative file linkage will be held in a different, secure location, and retained for as long until it is no longer needed for the processing of the survey data, after which it will be destroyed. All information released outside of Statistics Canada will conform to the confidentiality provisions of the Statistics Act.

Re-contact with the Saskatchewan justice system (052-2014)

Purpose: To determine the types of unique information required to create and support high quality indicators of re-contact within and across three criminal justice sectors. Whereas “contact” is defined as a documented official intervention (e.g. charge) against a person by a criminal justice agency/organization, a “re-contact” is defined as a subsequent contact signifying a new, official intervention by the agency/organization during a specified follow-up period.

The project will attempt to establish baseline metrics on re-contact with the justice system which can serve as a comparison group for assessing the impact of policies and programs which may be implemented in a particular jurisdiction. It will also provide the potential to be able to track emerging patterns of re-contact which may appear to be unique within a jurisdiction at a local level yet are more systematic in nature when evaluated at a higher level (e.g. national) of analysis.

Description: The record linkage will be used to support the development of re-contact indicators within and across the policing, courts and corrections sectors of justice.

The linkage will use records from three micro data surveys including those collected under the Uniform Crime Reporting (UCR2) Survey, the Integrated Criminal Court Survey (ICCS) and the Integrated Correctional Services Survey (ICSS).

The linkage will also use supplemental personal identifiers as provided by: several municipal police services in Saskatchewan and the Royal Canadian Mounted Police for the years January 1, 2006 to December 31, 2013; the Saskatchewan Ministry of Justice and Attorney General for the fiscal years 2006/2007 to 2012/2013; and, the Saskatchewan Ministry of Corrections for the fiscal years 2006/2007 to 2012/2013.

Output: Only non-confidential aggregate statistics and analyses conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. Access to linking keys and linked analysis file will be restricted to Statistics Canada employees whose assigned work activities require such access.

High-level and non-confidential findings may be reported in the form of presentations to various National Justice Statistics Initiative partners.

Statistics Canada will retain the linked analysis files until no longer required, up to, March 31, 2017, at which time the linked analysis files will be destroyed.

Business Performance Measurement of Various Programs for the Evaluation Directorate of the Federal Economic Development Agency for Southern Ontario (FedDev Ontario) – 2006 to 2013 (053-2014)

Purpose: The purpose of this linkage is to support the evaluation of FedDev Ontario programs by producing objective measures of their economic impacts on the performance on their client enterprises. Total expenses, total revenue, profits, change in debt ratio, working capital ratio, employment, R&D employment, and wages will be aggregated for FedDev Ontario client businesses and for comparable non-client businesses.

Description: A list of firms that were clients of FedDev Ontario programs during the period 2009 to 2013 will be linked to the Business Register to obtain the Business Number and Statistical Enterprise Number, to enable linkage to payroll, tax, R&D and export data. In order to measure the effectiveness and the impact of FedDev Ontario financing services, a comparison group of non-client firms with similar characteristics will be selected. The two groups will be compared using several business performance indicators derived from financial, employment, R&D and export data.

Records of program clients and the businesses in the comparison group will be linked to the Payroll Deduction Account (PD7), T1 Unincorporated Business Tax Data, T2 Corporate Tax data, Research and Data in Canadian Industry data and Exporter data. The records will be linked using the Business Number and Statistical Enterprise Number. The resulting linked analysis file will enable longitudinal analysis of each cohort. This is a one-time linkage.

Output: Only non-confidential aggregate statistical outputs and analyses that conform to the confidentiality provisions of the Statistics Actwill be released outside of Statistics Canada. These will be in the form of profiling tables giving total expenses, total revenue, profits, debt ratio, working capital ratio, employment, R&D employment, wages, exports, export intensity and survival rates for client and non-client businesses. A technical report will be prepared, explaining the file matching processes and constraints and key issues related to the quality of the data.

Linkage to the Canadian Mortality Database for the purposes of the PeriOperative Ischemic Evaluation (POISE Trial) Study (031-2014)

Purpose: The purpose of this study is to inform on the longer term risks and benefits to the patients at risk of a perioperative cardiovascular event who underwent non-cardiac surgery and who participated in a blinded randomized controlled trial of the drug metoprolol CR versus a placebo.

Description: The POISE Trial was a blinded randomized controlled trial of the drug metoprolol CR versus a placebo of patients at risk of a perioperative cardiovascular event (i.e. patients with atherosclerotic cardiovascular disease or with risk factors for atherosclerotic cardiovascular disease) who underwent non-cardiac surgery. Patients received the study drug two to four hours prior to surgery and subsequently for 30 days. The goal of the current record linkage project is to determine the long-term (i.e., 1 year) impact of this study intervention. A total of 23 countries participate in POISE. This record linkage involves only the Canadian participants.

A file consisting of records of those 3,539 patients who participated in the study in Canada will be linked by Statistics Canada to the 2002 to 2009 Canadian Mortality Database and to the 1984 to 2012 longitudinal T1 Personal Master File. The longitudinal T1 Personal Master File contains no income data, only information indicating whether individuals were alive or dead (and if dead, the date of death), if they emigrated or immigrated, and if taxes were filed during the study period.

Patients participating in the study signed consent forms granting the principal investigator consent for linkage of their records to mortality information.

Output: No analysis or publication of the results of this linkage will be conducted by Statistics Canada. A mortality output file will be produced, containing the clinical trial study number, complete date of death (month, day and year) and cause(s) of death.

The mortality output file will be split by province or territory of death, and the records will be sent to the appropriate vital statistics registrars who, at their discretion, will release the information to the principal investigator at the McMaster University.

The principal investigator has undertaken to publish the study findings in the form of aggregate statistical outputs that will not result in the identification of individual patients. Results of the analysis of the data will be presented at medical meetings and papers will be submitted to peer-reviewed medical journals for publication.

Access at Statistics Canada to the identifiers, linking keys and mortality output files will be restricted to employees whose assigned work requires such access. At no time will the information from the longitudinal T1 Personal Master File leave Statistics Canada, except in the form of aggregate tables.The linkage key file and mortality output file will be retained until no longer required, up to December 31, 2019, at which time these files will be destroyed.

The financial characteristics of Refugee Claimants in Canada (007-2014)

Purpose: The objective of this initiative is to create a database that will support research on the income characteristics of individuals who made a refugee claim in Canada during the 1990s or 2000s. The proposed file will include all refugee claimants, including those who did not subsequently become permanent residents in Canada as well as those who did. The data file will support research on the sources and amounts of income that refugee claimants receive.

Description: The data file will provide new information on refugee claimants by drawing together information for the years 1994 onward from: the Temporary Residents file from Social and Aboriginal Statistics Division at Statistics Canada, the Linkage Control File (LCF) developed and maintained by the Household Survey Methodology Division at Statistics Canada, the T5007 file from the Tax Data Division (TDD) at Statistics Canada, the T1 Historical File from TDD at Statistics Canada, and the T1 Family File from Income Statistics Division at Statistics Canada.

Output: Analytical findings resulting from the linked data file will be used to prepare tabulations and research papers for publication.

Only aggregate statistics and analysis conforming to the confidentiality provisions of the Statistics Act will be released outside of Statistics Canada. The output files will be retained by Statistics Canada until no longer required, up to, December 31, 2019, at which time they will be destroyed. All linkage keys and identifiers will be removed from the output files are retained separately, with access limited to Statistics Canada employees whose assigned work requires access to the file.

Linkage of the Industry Canada Database of Canadian Patents Filed in the United States Patent and Trademark Office (USPTO) 2000-2011 to the Linkable File Environment (LFE) (015-2014)

Purpose: The purpose of this record linkage is provide Industry Canada researchers and other researchers the opportunity to carry out policy relevant research using the data in the Industry Canada Database of Canadian Patents Filed in the United States Patent and Trademark Office (USPTO) to the Linkable File Environment (LFE) and the data available in other databases that are in the LFE.

Description: This is a request to link the Industry Canada Database of Canadian Patents Filed in the United States Patent and Trademark Office (USPTO) 2000-2011 to the Linkable File Environment (LFE).

Output: The linkable Industry Canada Database of Canadian Patents Filed in the United States Patent and Trademark Office (USPTO) will be housed at Statistics Canada's Centre for Special Business Project (CSBP). When a research project is formally approved by Statistics Canada, the CSBP will extract a researcher dataset from the LFE which will contain data for the variables that are listed in the research proposal for the population that has been specified. Access to the researcher datasets by external researchers will be facilitated and managed by Statistics Canada's Centre for Data Development and Economic Research (CDER).

Use of linkages between the 2001 and 2006 censuses and between the 2006 Census and the 2011 NHS/Census for analyses and projections of different population groups (006-2014)

Purpose: Existing linkages between the 2011 National Household Survey, 2011 Census and the 2006 Census (20% sample) and the linkage between the 2001 Census (20% sample) and 2006 Census (20% sample) would be used for analysis and projection purposes.

A number of Statistics Canada divisions—particularly the Demography Division, Social Analysis Division and Social and Aboriginal Statistics Division—would use the linkages to conduct analyses of various social phenomena, such as the ethnic mobility of Aboriginal people, analyses related to immigrants, and for any other analytical purpose that might require use of these data in the event that no other data source would enable such analyses.

The linkages would also be used to improve or create new parameters (inputs) to enhance the credibility and plausibility of assumptions and scenarios of demographic projections by microsimulation as part of the Demosim project (a microsimulation model created at Statistics Canada to produce projections of specific populations, such as visible minority groups or Aboriginal people), and to produce longitudinal socioeconomic indicators for immigrants and their descendants as part of an international project of the United Nations Economic Commission for Europe (UNECE) working group chaired by Statistics Canada.

Description: The first file to be used would be the one from the record linkage between the 2006 Census long-form questionnaire (20% sample), the 2011 Census and the 2011 National Household Survey. The matched database used would be the one created as part of a previously approved project.

The second file used would be the one created from linking records between the long-form questionnaire of the 2006 Census (20% sample) and the long-form questionnaire of the 2001 Census (20% sample). Once again, the matched database used would be the one created as part of a previously approved project.

Output: Under the Demosim project, the data produced will be used to prepare projection assumptions and parameters. The data used in preparing these assumptions and parameters, produced at an aggregate level, would be released, along with the methods used to produce them, in the form of technical documentation and/or scientific articles. Under the UNECE working group, the matched file of the 2006 Census and 2011 NHS would be used to prepare socioeconomic indicators for immigrants and their descendants which may be released.

The results from the different analyses that might be conducted  may also be disseminated in the form of analytical reports or articles.

In all cases, the data would only be disseminated in their aggregate form, in accordance with the confidentiality provisions of the Statistics Act. The linked files and linking keys will be retained until December 31, 2024 or before if they are no longer useful, after which they will be destroyed. The linked files will be retained in a secure directory on one of the Demography Division servers. Only employees whose work requires it will have access to this directory for the entire life of the files.