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All (2,481)

All (2,481) (40 to 50 of 2,481 results)

  • 41. Reverse-Engineering a Hypothetical Raking Process for the Estimation of Mean Squared Error of Raked Small Area Estimates Archived
    Articles and reports: 11-522-X202500100006
    Description: Small area estimation is frequently used to produce estimates at a disaggregated level where direct survey estimation does not have sufficient sample to produce precise estimates. Often this is done using the area-level Fay-Herriot model, by assuming the direct estimates are independent under the design and have a known variance, and applying a smoothing process to the variance estimates of the direct estimates to better meet that last assumption. It is not rare that small area estimates are benchmarked/raked to aggregated level direct estimates. This article shows that wrongly assuming independence can have a big impact on the MSE of the raked estimates. Values of the covariances between direct estimates are thus required for good point and MSE estimates. Getting good estimates of those covariances is difficult given the small sample sizes in some areas. An original way of deriving values for those covariances, by reverse-engineering a hypothetical raking process, is presented.
    Release date: 2025-09-08
  • 42. Correcting Selection Bias in a Non-probability Two-phase Payment Survey Archived
    Articles and reports: 11-522-X202500100007
    Description: This paper employs the Pseudo Maximum Likelihood (PML) estimator to the non-probability two-phase sampling when relevant auxiliary information is available from both probability survey sample and non-probability survey sample. To accommodate various weight adjustments and estimates variance beyond totals and means such as medians and quantiles, a simplified pseudo-population bootstrap procedure is proposed to approximately estimate the second-phase variance. Specifically, the simplification ignores the second phase sampling variability (i.e., treated as fixed, while in fact it is random), if the first-phase sampling fraction of the non-probability sample is negligible. Using the Bank of Canada 2020 Cash Alternative Survey Wave 2, the performance of the proposed method is compared to alternative methods, which either do not explicitly model the selection probability (i.e., raking) or ignore the valuable information from Phase 1 (i.e., Phase-2-Only). The results show that the PML-based approach performs better than raking and Phase-2-Only estimates in terms of reducing the selection bias for both phases' payment-related variables, especially for the low-response youth group. Estimated variances of the PML-based estimates are stable.

    Release date: 2025-09-08
  • 43. Recruitment and Collection of Web Panels at Statistics Canada Archived
    Articles and reports: 11-522-X202500100008
    Description: In 2020, Statistics Canada started to use probabilistic web panels as an alternate method of collecting official statistics. In a web panel, respondents to another survey are asked for contact information to participate in future short surveys. This paper will highlight Statistics Canada's experience with panels after 4 years, including what has been learned about the recruitment of panel participants and how to subsequently collect data using panel surveys. The ways in which recruitment questions are presented can result in very different rates of participation. Moreover, the wealth of auxiliary information available on the recruitment survey can be used to actively manage panel collection operations, by predicting the probability of response and using this information to target follow-up efforts.
    Release date: 2025-09-08
  • 44. A Bias Evaluation for Probabilistic Web Panels at Statistics Canada Archived
    Articles and reports: 11-522-X202500100009
    Description: Three series of web panels were implemented at Statistics Canada from 2020 to 2024. Participants for these web panel series were recruited from respondents of large probabilistic social surveys (recruitment surveys), and subsequently were invited to complete a series of short online surveys. Estimates of recruitment survey variables were calculated using both recruitment survey weights and web panel weights, and these were compared; differences signal the possibility of residual bias that was not corrected by the web panel weighting process. This investigation found more significant differences than would be expected if the web panel estimator fully corrected for the bias resulting from the web panel response process. Questions related to certain topics such as politics and voting, sense of belonging, and media consumption were found to have the most significant differences between web panel estimates and recruitment survey estimates.
    Release date: 2025-09-08
  • 45. Life in the FastText Lane: Harnessing Linear Programming Constrained Machine Learning for Classifications Revision Archived
    Articles and reports: 11-522-X202500100010
    Description: Statistics Canada's Labour Force Survey (LFS) plays an essential role in the estimation of labour market conditions in Canada. Periodically, LFS revises its data to the most recent industry and occupational classification versions. Differences in versions can be extensive, including high-level and unit-group structural changes, creations, deletions, split-offs and combination of classification units (classes). Historically, to reconcile split-off classes - where one class splits into multiple classes - a sample of LFS split-off records would be manually recoded to the new classification version. Based on the split-off proportion observed in the recoded sample, a random allocation method would be applied on all data to reflect the changing Canadian labour market over time. This article proposes using machine learning (fastText), constrained to split-off proportions using linear programming, to revise industry and occupation classifications in LFS. The hybrid framework benefits from a text-based revision mechanism while adhering to traditional proportions driven estimates, thus ensuring a minimal impact on the comparability of published labour market indicators.
    Release date: 2025-09-08
  • 46. Data-driven Imputation Strategies and their Associated Quality Indicators in Economic Surveys Archived
    Articles and reports: 11-522-X202500100011
    Description: The use of modern "data"-driven imputation methods to treat non-response in the context of surveys processed in the Integrated Business Statistics Program at Statistics Canada has previously been explored. It was observed that these methods can lead to high quality imputation and further have the potential to result in broad efficiencies when setting up a particular survey's edit and imputation strategy. However, estimation of the associated total variance, more specifically the component due to imputation, remains a challenge. In this article, two methods for estimation of total variance are proposed and show preliminary results that have motivated us to pursue further research in this area.
    Release date: 2025-09-08
  • 47. The challenges of conducting a survey of youth in Nunavik UVIKKAVUT QANUIPPAT? Archived
    Articles and reports: 11-522-X202500100012
    Description: In 2022, the Institut de la statistique du Québec conducted a survey of high school students in Nunavik, a unique, remote region of Quebec. The survey aimed to develop a portrait of the state of the students' physical and mental health, their lifestyle habits and their environment. This article describes the challenges encountered during the survey and the solutions put in place to overcome them.
    Release date: 2025-09-08
  • 48. Advancing Equitable Data Collection: Insights from Statistics Canada's Statistical Integration Methods Division Disaggregated Data Action Plan Research Project Archived
    Articles and reports: 11-522-X202500100013
    Description: As part of answering the call to action for the United Nations' (UN) 17 Sustainable Development Goals, as well as addressing social, economic, and equity challenges within Canada, Statistics Canada's five-year development phase for the Disaggregated Data Action Plan (DDAP) was funded in 2021 to support data driven decision around these challenges. In turn, the document "Guiding Principles: Leveraging the 2021 Census of Populations Data for DDAP Groups of Interest" were created. The guiding principles document explains the organizational framework of the DDAP in the Agency, describes existing data sources, addresses ethical and privacy concerns, and centralizes sampling methods tailored for DDAP initiatives while accounting for characteristics which can complicate sampling and data collection procedures.
    Release date: 2025-09-08
  • 49. On the Interplay of Legal Requirements, Quality Aspects and Ethical Risks when using Machine Learning in German Official Statistics Archived
    Articles and reports: 11-522-X202500100014
    Description: Artificial intelligence (AI) with its subfield machine learning (ML) has found its way into administration in general and also into official statistics in Germany in particular. This paper highlights the ethical issues that may arise when using AI/ML in official statistics and examines whether a separate ethical framework is needed to deal with these issues appropriately, as is proposed by institutions of other countries and intergovernmental institutions related to official statistics. The results of the study are presented to show that the implementation of the requirements of the existing and mostly non-AI/ML-specific frames of reference such as law and quality is already sufficient to adequately address the ethical issues based on risk scenarios.
    Release date: 2025-09-08
  • 50. Statistical Disclosure Control Analysis for Small Area Estimation Archived
    Articles and reports: 11-522-X202500100015
    Description: Currently, Statistics Canada has no official guidance on confidentiality rules for releasing small area estimate. In recent years, there has been increasing demand from Research Data Centre (RDC) researchers for comprehensive confidentiality guidelines such that they can publish small area estimates in their research. This confidentiality analysis applies to area-level small area estimation.
    Release date: 2025-09-08
Data (10)

Data (10) ((10 results))

  • 1. Social Policy Simulation Database and Model (SPSD/M)
    Public use microdata: 89F0002X
    Description: The SPSD/M is a static microsimulation model designed to analyse financial interactions between governments and individuals in Canada. It can compute taxes paid to and cash transfers received from government. It is comprised of a database, a series of tax/transfer algorithms and models, analytical software and user documentation.
    Release date: 2026-02-12
  • 2. National Address Register
    Profile of a community or region: 46-26-0002
    Description: The National Address Register (NAR) is a list of commercial and residential addresses in Canada that are extracted from Statistics Canada's Building Register and deemed non-confidential.
    Release date: 2025-12-19
  • 3. PASSAGES microsimulation model
    Table: 89-26-0006
    Description: PASSAGES is an open-source dynamic microsimulation model aimed at supporting policy analysis and research relating to Canadian retirement income system outcomes at the individual and family level. The publicly available version includes a synthetic starting database, a model, and documentation. A confidential starting database is also available.
    Release date: 2025-03-12
  • 4. Canadian Statistical Geospatial Explorer Hub Archived
    Data Visualization: 71-607-X2020010
    Description: The Canadian Statistical Geospatial Explorer empowers users to discover geo enabled data holdings of Statistics Canada at various levels of geography including at the neighbourhood level. Users are able to visualize, thematically map, spatially explore and analyze, export and consume data in various formats. Users can also view the data superimposed on satellite imagery, topographic and street layers.
    Release date: 2024-08-21
  • 5. Income divergence index (D-index) by census tract
    Table: 11-10-0074-01
    Geography: Census tract
    Frequency: Occasional
    Description:

    The divergence index (D-index) describes the degree that families with different income levels are mixing together in neighbourhoods. It compares neighbourhood (census tract, CT) discrete income distributions to a base distribution, which is the income quintiles of the neighbourhood’s census metropolitan area (CMA).

    Release date: 2020-06-22
  • 6. Housing Data Viewer Archived
    Data Visualization: 71-607-X2019010
    Description: The Housing Data Viewer is a visualization tool that allows users to explore Statistics Canada data on a map. Users can use the tool to navigate, compare and export data.
    Release date: 2019-10-30
  • 7. Findings of the Canadian Vehicle Fuel Pilot Survey Archived
    Table: 53-500-X
    Description:

    This report presents the results of a pilot survey conducted by Statistics Canada to measure the fuel consumption of on-road motor vehicles registered in Canada. This study was carried out in connection with the Canadian Vehicle Survey (CVS) which collects information on road activity such as distance traveled, number of passengers and trip purpose.

    Release date: 2004-10-21
  • 8. National Tourism Indicators, Historical Estimates Archived
    Table: 13-220-X
    Description: In the 1997 edition, new and revised benchmarks were introduced for 1992 and 1988. The indicators are used to monitor supply, demand and employment for tourism in Canada on a timely basis. The annual tables are derived using the National Income and Expenditure Accounts (NIEA) and various industry and travel surveys. Tables providing actual data and percentage changes, for seasonally adjusted current and constant price estimates are included. In addition, an analytical section provides graphs, and time series of first differences, percentage changes, and seasonal factors for selected indicators. Data are published from 1987 and the publication will be available on the day of release. New data are included in the demand tables for non-tourism commodities produced by non-tourism industries and in the employment tables covering direct tourism employment generated by non-tourism industries. This product was commissioned by the Canadian Tourism Commission to provide annual updates for the Tourism Satellite Account.
    Release date: 2003-01-08
  • 9. Historical Statistics of Canada Archived
    Table: 11-516-X
    Description:

    The second edition of Historical statistics of Canada was jointly produced by the Social Science Federation of Canada and Statistics Canada in 1983. This volume contains about 1,088 statistical tables on the social, economic and institutional conditions of Canada from the start of Confederation in 1867 to the mid-1970s. The tables are arranged in sections with an introduction explaining the content of each section, the principal sources of data for each table, and general explanatory notes regarding the statistics. In most cases, there is sufficient description of the individual series to enable the reader to use them without consulting the numerous basic sources referenced in the publication.

    The electronic version of this historical publication is accessible on the Internet site of Statistics Canada as a free downloadable document: text as HTML pages and all tables as individual spreadsheets in a comma delimited format (CSV) (which allows online viewing or downloading).

    Release date: 1999-07-29
  • 10. National Population Health Survey Overview Archived
    Table: 82-567-X
    Description:

    The National Population Health Survey (NPHS) is designed to enhance the understanding of the processes affecting health. The survey collects cross-sectional as well as longitudinal data. In 1994/95 the survey interviewed a panel of 17,276 individuals, then returned to interview them a second time in 1996/97. The response rate for these individuals was 96% in 1996/97. Data collection from the panel will continue for up to two decades. For cross-sectional purposes, data were collected for a total of 81,000 household residents in all provinces (except people on Indian reserves or on Canadian Forces bases) in 1996/97.

    This overview illustrates the variety of information available by presenting data on perceived health, chronic conditions, injuries, repetitive strains, depression, smoking, alcohol consumption, physical activity, consultations with medical professionals, use of medications and use of alternative medicine.

    Release date: 1998-07-29
Analysis (2,037)

Analysis (2,037) (60 to 70 of 2,037 results)

  • 61. Statistics Canada International Symposium Series: Proceedings
    Journals and periodicals: 11-522-X
    Description: Since 1984, an annual international symposium on methodological issues has been sponsored by Statistics Canada. Proceedings have been available since 1987.
    Release date: 2025-09-08
  • 62. A conversation with Geoffrey Hole
    Articles and reports: 12-001-X202500100001
    Description: Geoffrey J.C. Hole (or Geoff, as he likes to be called) was born on January 24, 1940 at Shardeloes, Amersham, Buckinghamshire, England, to Charles William Hole and Sybil Winifred Hole, formerly Morge. He completed a BSc Honours in Mathematics in 1961, and a Postgraduate Diploma in Statistics at Manchester University the following year. He started his career as a mathematical statistician in London, England, working successively for the National Coal Board (1962-63), the Central Electricity Generating Board (1963-66), and the Electricity Council (1966-67), where his title was Economist. He moved to Canada in 1967 to join the Dominion Bureau of Statistics (DBS) as a survey methodologist. In 1971-72, he was Chief of Census Operations, Methodology and Quality Control Section, and Assistant Coordinator, Socio-Economic Survey Methods Section. He then took a one-year leave of absence to complete an MSc (Econ) in Statistics at the London School of Economics. In 1973, Geoff returned to the DBS, which had become Statistics Canada, as Chief, Methodology Group V, Business Survey Methods Division. In 1974, he was appointed Director, Institutions and Agriculture Survey Methods Division, and, as of 1986, Director, Business Survey Methods Division. His career culminated when he became Director, Social Survey Methods Division, in 1987. He held that position until his retirement, on September 29, 2004. In addition to his long-term involvement at Statistics Canada, including as a member of the Editorial Board of Survey Methodology between 1983 and 1987, Geoff was very active in the Statistical Society of Canada (SSC), serving among others as Chair of the Program Committee for the 1986 Annual Meeting at the Banff Centre, in Alberta, and President of the SSC in 1989-90. He was also Program Chair for a joint conference of the International Association of Survey Statisticians and the International Association for Official Statistics which was held in Aguascalientes, Mexico, in 1998.
    Release date: 2025-06-30
  • 63. A conversation with Dr. Ivan P. Fellegi
    Articles and reports: 12-001-X202500100002
    Description: Ivan Fellegi is an expert in statistical science and a public servant who was the Chief Statistician of Canada from 1985 to 2008. This article briefly recounts his early life, long-spanning career and influential research contributions. It includes an interview conducted in February 2017 to mark the 60th year of service of Ivan Fellegi’s career at Statistics Canada.
    Release date: 2025-06-30
  • 64. On the use of machine learning methods for the treatment of unit nonresponse in surveys
    Articles and reports: 12-001-X202500100003
    Description: In recent years, there has been a significant interest in machine learning in national statistical offices. Thanks to their flexibility, these methods may prove useful at the nonresponse treatment stage. In this article, we conduct an empirical investigation in order to compare several machine learning procedures in terms of bias and efficiency. In addition to the classical machine learning procedures, we assess the performance of ensemble approaches that make use of different machine learning procedures to produce a set of weights adjusted for nonresponse.
    Release date: 2025-06-30
  • 65. Imputation of nonignorable missing data in surveys using auxiliary margins via hot deck and sequential imputation
    Articles and reports: 12-001-X202500100004
    Description: Survey data collection often is plagued by unit and item nonresponse. To reduce reliance on strong assumptions about the missingness mechanisms, statisticians can use information about population marginal distributions known, for example, from censuses or administrative databases. One approach that does so is the Missing Data with Auxiliary Margins, or MD-AM, framework, which uses multiple imputation for both unit and item nonresponse so that survey-weighted estimates accord with the known marginal distributions. However, this framework relies on specifying and estimating a joint distribution for the survey data and nonresponse indicators, which can be computationally and practically daunting in data with many variables of mixed types. We propose two adaptations to the MD-AM framework to simplify the imputation task. First, rather than specifying a joint model for unit respondents’ data, we use random hot deck imputation while still leveraging the known marginal distributions. Second, instead of sampling from conditional distributions implied by the joint model for the missing data due to item nonresponse, we apply multiple imputation by chained equations for item nonresponse before imputation for unit nonresponse. Using simulation studies with nonignorable missingness mechanisms, we demonstrate that the proposed approach can provide more accurate point and interval estimates than models that do not leverage the auxiliary information. We illustrate the approach using data on voter turnout from the U.S. Current Population Survey.
    Release date: 2025-06-30
  • 66. Mean squared prediction error estimators of the empirical best linear unbiased predictor of a small area mean under a semi-parametric Fay-Herriot model
    Articles and reports: 12-001-X202500100005
    Description: In this paper, we derive a second-order unbiased (or nearly unbiased) mean squared prediction error (MSPE) estimator of the empirical best linear unbiased predictor (EBLUP) of a small area mean for a semi-parametric extension to the well-known Fay-Herriot model. Specifically, we derive our MSPE estimator essentially assuming certain moment conditions on both the sampling errors and random effects distributions. The normality-based Prasad-Rao MSPE estimator has a surprising robustness property in that it remains second-order unbiased under the non-normality of random effects when a simple Prasad-Rao method-of-moments estimator is used for the variance component and the sampling error distribution is normal. We show that the normality-based MSPE estimator is no longer second-order unbiased when the sampling error distribution has non-zero kurtosis or when the Fay-Herriot moment method is used to estimate the variance component, even when the sampling error distribution is normal. Interestingly, when the simple method-of moments estimator is used for the variance component, our proposed MSPE estimator does not require the estimation of kurtosis of the random effects. Results of a simulation study on the accuracy of the proposed MSPE estimator, under non-normality of both sampling and random effects distributions, are also presented.
    Release date: 2025-06-30
  • 67. sCHAID: A tool for constructing nonresponse adjustment cells under a design-based framework
    Articles and reports: 12-001-X202500100006
    Description: Survey practitioners have increasingly embraced the benefits of modern machine learning techniques, including classification and regression tree algorithms, in the development of nonresponse adjustments. These methods, which do not require a predefined functional relationship between outcomes and predictors, offer a practical means of conducting variable selection and deriving interpretable structures that link response propensity with explanatory variables. However, when applying these algorithms to survey data, it is common to overlook crucial factors like sampling weights, as well as sample design features such as stratification and clustering. To bridge this shortcoming, we propose an extension of the Chi-square Automatic Interaction Detector (CHAID) approach, and we describe the design-based asymptotic properties of the resulting “survey CHAID” (sCHAID) method. To facilitate the practical use of sCHAID, we incorporate a Rao-Scott correction into the splitting criterion, accounting for the survey design. Using data from the U.S. American Community Survey, we illustrate the use of the method and evaluate its performance through comparisons with existing weighted and unweighted algorithms.
    Release date: 2025-06-30
  • 68. Model-assisted calibration estimation using generalized entropy calibration in survey sampling
    Articles and reports: 12-001-X202500100007
    Description: We introduce a novel approach to model-assisted calibration estimation in survey sampling using generalized entropy. The method builds upon recent work by Kwon, Kim and Qiu (2024) and extends it to a model-assisted framework. Unlike traditional calibration techniques, this approach employs a generalized entropy function as the objective for optimization and incorporates a debiasing calibration constraint to ensure design consistency. The proposed estimator is shown to be asymptotically equivalent to an augmented generalized regression (GREG) estimator. It allows for unequal model variance, potentially improving efficiency when the sampling design is informative. The paper presents both design-based and model-based justifications for the method, along with asymptotic properties and variance estimation techniques. Computational aspects are discussed, including an unconstrained optimization approach that facilitates implementation, especially for high-dimensional auxiliary variables. The method’s performance is evaluated through a simulation study, demonstrating its effectiveness in improving estimation efficiency, particularly when the sampling design is informative.
    Release date: 2025-06-30
  • 69. Use of nonprobability samples for official statistics, state of the art
    Articles and reports: 12-001-X202500100008
    Description: Tightened budgets, continuing decrease of response rates in traditional probability surveys and increasing pressure by users for more timely data, has stimulated research on the use of nonprobability sample data, such as administrative records, web scraping, mobile phone data and voluntary internet surveys, for inference on finite population parameters like means and totals. These data are often easier, faster and cheaper to collect than traditional probability samples. However, a major concern with the use of this kind of data for official statistics is their nonrepresentativeness due to possible selection bias, which if not accounted for properly, could bias the inference. In this article, we review and discuss methods considered in the literature to deal with this problem and propose new methods, distinguishing between methods based on integration of the nonprobability sample with an appropriate probability sample, and methods that base the inference solely on the nonprobability sample. Empirical illustrations, based on simulated data are provided.
    Release date: 2025-06-30
  • 70. Bridging BigData and sampling methodology: What is big and where is the bridge?
    Articles and reports: 12-001-X202500100009
    Description: BigData users and the BigData research community are expanding rapidly, while statisticians at large are seemingly becoming divided between those who are enthusiastic and those who are concerned, if not downright hostile. Is BigData also a big step ahead, truly advancing our ability to extract meaningful information and actual knowledge from data? Is BigData underplaying traditional statistical inference as we know it, supplanting survey methodology as a low-cost futuristic option? In this paper I will attempt to unravel the multifaceted relationship bridging BigData to sampling methodology. Starting by reasoning why it should be interesting to look at BigData from a sampling statistician’s perspective, I will delve deeper into the somewhat ambiguous definition of BigData and share some very personal considerations and views on the matter. In the process, several open questions will arise while discussing a personal selection of insights that are traceable through the vast body of statistical literature around BigData and sampling methodology. The discussion will take various angles explored across nine key points, and it will conclude with a forward-looking perspective on a main challenge for future research: addressing the strong assumptions needed to manage deviations from purely randomized data collection.
    Release date: 2025-06-30
Reference (382)

Reference (382) (60 to 70 of 382 results)

  • 61. Using data linkage to evaluate the consistency of place of residence between census data and tax data Archived
    Surveys and statistical programs – Documentation: 11-522-X201700014725
    Description:

    Tax data are being used more and more to measure and analyze the population and its characteristics. One of the issues raised by the growing use of these type of data relates to the definition of the concept of place of residence. While the census uses the traditional concept of place of residence, tax data provide information based on the mailing address of tax filers. Using record linkage between the census, the National Household Survey and tax data from the T1 Family File, this study examines the consistency level of the place of residence of these two sources and its associated characteristics.

    Release date: 2016-03-24
  • 62. Estimating internal migration: Issues related to using tax data Archived
    Surveys and statistical programs – Documentation: 11-522-X201700014726
    Description:

    Internal migration is one of the components of population growth estimated at Statistics Canada. It is estimated by comparing individuals’ addresses at the beginning and end of a given period. The Canada Child Tax Benefit and T1 Family File are the primary data sources used. Address quality and coverage of more mobile subpopulations are crucial to producing high-quality estimates. The purpose of this article is to present the results of evaluations of these elements using access to more tax data sources at Statistics Canada.

    Release date: 2016-03-24
  • 63. An Overview of Business Record Linkage at Statistics Canada: How to link the “Unlinkable” Archived
    Surveys and statistical programs – Documentation: 11-522-X201700014741
    Description:

    Statistics Canada’s mandate includes producing statistical data to shed light on current business issues. The linking of business records is an important aspect of the development, production, evaluation and analysis of these statistical data. As record linkage can intrude on one’s privacy, Statistics Canada uses it only when the public good is clear and outweighs the intrusion. Record linkage is experiencing a revival triggered by a greater use of administrative data in many statistical programs. There are many challenges to business record linkage. For example, many administrative files not have common identifiers, information is recorded is in non-standardized formats, information contains typographical errors, administrative data files are usually large in size, and finally the evaluation of multiple record pairings makes absolute comparison impractical and sometimes impossible. Due to the importance and challenges associated with record linkage, Statistics Canada has been developing a record linkage standard to help users optimize their business record linkage process. For example, this process includes building on a record linkage blocking strategy that reduces the amount of record-pairs to compare and match, making use of Statistics Canada’s internal software to conduct deterministic and probabilistic matching, and creating standard business name and address fields on Statistics Canada’s Business Register. This article gives an overview of the business record linkage methodology and looks at various economic projects which use record linkage at Statistics Canada, these include projects in the National Accounts, International Trade, Agriculture and the Business Register.

    Release date: 2016-03-24
  • 64. Redesign of the longitudinal immigration database (IMDB) Archived
    Surveys and statistical programs – Documentation: 11-522-X201700014747
    Description:

    The Longitudinal Immigration Database (IMDB) combines the Immigrant Landing File (ILF) with annual tax files. This record linkage is performed using a tax filer database. The ILF includes all immigrants who have landed in Canada since 1980. In looking to enhance the IMDB, the possibility of adding temporary residents (TR) and immigrants who landed between 1952 and 1979 (PRE80) was studied. Adding this information would give a more complete picture of the immigrant population living in Canada. To integrate the TR and PRE80 files into the IMDB, record linkages between these two files and the tax filer database, were performed. This exercise was challenging in part due to the presence of duplicates in the files and conflicting links between the different record linkages.

    Release date: 2016-03-24
  • 65. Use of Administrative Data to Increase the Efficiency of the Sample Design for the New National Travel Survey Archived
    Surveys and statistical programs – Documentation: 11-522-X201700014749
    Description:

    As part of the Tourism Statistics Program redesign, Statistics Canada is developing the National Travel Survey (NTS) to collect travel information from Canadian travellers. This new survey will replace the Travel Survey of Residents of Canada and the Canadian resident component of the International Travel Survey. The NTS will take advantage of Statistics Canada’s common sampling frames and common processing tools while maximizing the use of administrative data. This paper discusses the potential uses of administrative data such as Passport Canada files, Canada Border Service Agency files and Canada Revenue Agency files, to increase the efficiency of the NTS sample design.

    Release date: 2016-03-24
  • 66. Challenges Associated with Using Scanner Data for the Consumer Price Index Archived
    Surveys and statistical programs – Documentation: 11-522-X201700014751
    Description:

    Practically all major retailers use scanners to record the information on their transactions with clients (consumers). These data normally include the product code, a brief description, the price and the quantity sold. This is an extremely relevant data source for statistical programs such as Statistics Canada’s Consumer Price Index (CPI), one of Canada’s most important economic indicators. Using scanner data could improve the quality of the CPI by increasing the number of prices used in calculations, expanding geographic coverage and including the quantities sold, among other things, while lowering data collection costs. However, using these data presents many challenges. An examination of scanner data from a first retailer revealed a high rate of change in product identification codes over a one-year period. The effects of these changes pose challenges from a product classification and estimate quality perspective. This article focuses on the issues associated with acquiring, classifying and examining these data to assess their quality for use in the CPI.

    Release date: 2016-03-24
  • 67. Report on Plans and Priorities
    Surveys and statistical programs – Documentation: 11-018-X
    Description: Reports on Plans and Priorities (RPP) are individual expenditure plans for each department and agency. These reports provide increased levels of detail over a three-year period on an organization's main priorities by strategic outcome, program and planned/expected results, including links to related resource requirements presented in the Main Estimates. In conjunction with the Main Estimates, Reports on Plans and Priorities serve to inform members of Parliament on planned expenditures of departments and agencies, and support Parliament's consideration of supply bills. The RPPs are typically tabled soon after the Main Estimates by the President of the Treasury Board.
    Release date: 2016-03-07
  • 68. A New Survey Measure of Disability: the Disability Screening Questions (DSQ) Archived
    Surveys and statistical programs – Documentation: 89-654-X2016003
    Description:

    This paper describes the process that led to the creation of the new Disability Screening Questions (DSQ), jointly developped by Statistics Canada and Employment and Social Development Canada. The DSQ form a new module which can be put on general population surveys to allow comparisons of persons with and without a disability. The paper explains why there are two versions of the DSQ—a long and a short one—, the difference between the two, and how each version can be used.

    Release date: 2016-02-29
  • 69. Revisions to 2006 to 2011 income data Archived
    Surveys and statistical programs – Documentation: 75F0002M2015003
    Description:

    This note discusses revised income estimates from the Survey of Labour and Income Dynamics (SLID). These revisions to the SLID estimates make it possible to compare results from the Canadian Income Survey (CIS) to earlier years. The revisions address the issue of methodology differences between SLID and CIS.

    Release date: 2015-12-17
  • 70. Methodology for measuring the underground economy by province and territory Archived
    Surveys and statistical programs – Documentation: 13-605-X201500414166
    Description:

    Estimates of the underground economy by province and territory for the period 2007 to 2012 are now available for the first time. The objective of this technical note is to explain how the methodology employed to derive upper-bound estimates of the underground economy for the provinces and territories differs from that used to derive national estimates.

    Release date: 2015-04-29

Sort Help

How are the results ordered?

The Sort by feature provides four options:

  • By date – sorts results by product release date starting with the most recent.
  • By most popular – gives priority to results that are most frequently selected by users, followed by the most recent.
  • By relevance is only needed or beneficial when you use the search box and submit a search query. Results are ordered by a combination of where the search term appears in the content, e.g., if it appears in the title, it likely means the product is more relevant to your search; how up to date or new the content in the product is; how popular the product is; and other factors.
  • By title – sorts results alphabetically.

Sort Help

How are the results ordered?

The Sort by feature provides three options:

  • By date – sorts results by product release date starting with the most recent.
  • By relevance is only needed or beneficial when you use the search box and submit a search query. Results are ordered by a combination of where the search term appears in the content, e.g., if it appears in the title, it likely means the product is more relevant to your search; how up to date or new the content in the product is; how popular the product is; and other factors.
  • By title – sorts results alphabetically.

Search Help

How do I use the filters and the search box?

  • You can initiate a search by entering keywords or selecting filters (e.g., under Subject, Geography, etc.) on the left side of the page.

  • Filters can be used together or in any combination. Each time you select a filter, the results on the page are updated.

  • To start a new search, click on the Clear all button above the search box or deselect each filter.

  • Specified keywords and filters appear above the search box. You can deselect any or all the tags to refine or clear your search.

How do I refine my search?

  • You can enter keywords in the search box. It is not necessary to use “+” or “, “ or “AND”.

  • You can delete some or all of the keywords from your search string.

  • Quotes around keywords limit the search to a specific phrase.

    • For example, “labour force survey” will limit results to products containing this phrase.

  • Use “or” between keywords to obtain results that contain one or more search terms.

    • For example, labour or­ force or survey will limit results to products containing any or all of these words.

How does the search work?

  • This search looks for results that have your query term in the title, description, subject, geography, product number or other information about the product.

    • For example, when searching the term ‘Diseases’, all results with the word ‘Diseases’ in the title, description or tagged the subject appear.

  • The text within an article or publication are not searched. For full text searching of articles, use the site search.

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