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All (2,478) (40 to 50 of 2,478 results)

  • 41. 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
  • 42. 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
  • 43. 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
  • 44. 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
  • 45. 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
  • 46. 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
  • 47. 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
  • 48. Synthetic Data Disclosure Risk Assessment: A Literature Review Archived
    Articles and reports: 11-522-X202500100016
    Description: The adoption of synthetic data generation as a confidentiality measure is increasing in statistical agencies worldwide, including at Statistics Canada. This approach provides an alternative to the traditional dissemination of anonymized public microdata files, offering both privacy protection and data utility. However, the creation of synthetic data presents challenges in assessing and mitigating disclosure risks. This paper reviews the different types of disclosure risks, that being attribute, membership and identity disclosure, and presents some of the associated methods for measuring risk. The paper presents prominent risk assessment metrics and discusses practical methods for disclosure control in data synthesis. Methods for assessing disclosure risks usually produce a metric that can be used to gauge the risk, but there is little consensus on threshold values for these metrics. It is also important to focus on importance of balancing utility and confidentiality, which needs further discussion in context of these methods. The paper concludes by offering insights and recommendations about managing disclosure risk while creating synthetic data as well as providing some ideas on future directions for research and practical implications for managing disclosure risks in synthetic data.
    Release date: 2025-09-08
  • 49. Exploration of Deep Learning Synthetic Data Generation for Sensitive Utility Data Sharing Archived
    Articles and reports: 11-522-X202500100017
    Description: Utilities hold crucial information about energy usage and building characteristics which can be utilized by government agencies to improve their corresponding analytics. However, this data is associated with private customer records and thus the building data and energy usage may be too sensitive to share. Often, high-level aggregated versions of this data are shared through robust contracts, limiting the statistics that can be derived. With the advancement of generative machine learning techniques, Statistics Canada and Natural Resources Canada have explored the feasibility of using these models to produce synthetic versions of utility data which may be shared in full to requesting organizations. These synthetic datasets can be created by a utility company through a locally run program and the outputs can be approved before being sent. This work has identified that certain generative models can feasibly be used by utilities to generate new versions of a dataset and has identified the issues which must be addressed prior to implementing this in practice. Both tabular and time-series models have been tested for different data sharing scenarios, where the TimeGAN model successfully captured the general energy peaks and valleys over a given day with reasonable computational requirements. Although this process takes days for annual energy amounts over thousands of customer records, this can enable new data sharing initiatives between utilities and National Statistical Offices while managing privacy risks. As work progresses in future phases with real utility partners, trust can be built for these approaches, and they can begin being tested on real data by actual data holders.
    Release date: 2025-09-08
  • 50. Survey-admin Hybrid Measure of Persistent Child Poverty in New Zealand Archived
    Articles and reports: 11-522-X202500100018
    Description: The Child Poverty Reduction Act (2018) outlines a need for the New Zealand Government to set three- and ten-yearly persistent child poverty reduction targets come end of 2024. In the absence of longitudinal survey data, a survey-administrative data hybrid method that will facilitate the production of these reduction targets and official estimates of persistent child poverty once reporting is required for the 2025/2026 financial year onwards is outlined. This hybrid approach leverages off the cross-sectional Household Economic Survey (HES), administrative-based beneficiary's family data, and recent advances developed for the construction of households within the Administrative Population Census (APC) at Statistics New Zealand. With increasing data collection challenges due to rising non-response and costs, this survey-admin hybrid method represents an alternative to longitudinal survey data collection, ensuring ongoing sustainable and quality statistics to produce persistent child poverty estimates.
    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 (2,036)

Analysis (2,036) (0 to 10 of 2,036 results)

  • 1. Statistical Methods Reference Documents
    Surveys and statistical programs – Documentation: 19-20-0001
    Description: Documents in this series provide insight into the statistical methods used by Statistics Canada to produce official statistics. They include introductory material, in-depth descriptions of techniques and methods, best practices, and guidelines. All documents have undergone review to ensure that they conform to Statistics Canada's mandate and adhere to generally accepted methodological standards and practices.
    Release date: 2026-05-11
  • 2. Analytical Studies: Methods and References
    Journals and periodicals: 11-633-X
    Description: Papers in this series provide background discussions of the methods used to develop data for economic, health, and social analytical studies at Statistics Canada. They are intended to provide readers with information on the statistical methods, standards and definitions used to develop databases for research purposes. All papers in this series have undergone peer and institutional review to ensure that they conform to Statistics Canada's mandate and adhere to generally accepted standards of good professional practice.
    Release date: 2026-04-24
  • 3. Distributions of Household Economic Accounts, estimates of asset, liability and net worth distributions, 2010 to 2025, technical methodology and quality report
    Articles and reports: 13-604-M2026001
    Description: This documentation outlines the methodology used to develop the Distributions of household economic accounts published in January 2026 for the reference years 2010 to 2025. It describes the framework and the steps implemented to produce distributional information aligned with the National Balance Sheet Accounts and other national accounts concepts. It also includes a report on the quality of the estimated distributions.
    Release date: 2026-01-29
  • 4. Effects of model misspecification on small area estimators
    Articles and reports: 12-001-X202500200001
    Description: Nested error regression models are commonly used to incorporate unit specific auxiliary variables to improve small area estimates. When the mean structure of the model is misspecified, the design-based mean squared prediction error (MSPE) of Empirical Best Linear Unbiased Predictors (EBLUP) generally increases. The Observed Best Prediction (OBP) method has been proposed with the intent to improve on the design-based MSPE over EBLUP. In this paper, we conduct a Monte Carlo simulation experiments to understand the effect of misspsecification of mean structures on different small area estimators. Our findings suggest that the OBP using unit-level auxiliary variables does not outperform the EBLUP in terms of design-based MSPE, unless the number of small areas m is extremely large. Conversely, the performance of OBP significantly improves when area-level auxiliary variables are employed. This paper includes both analytical and numerical evidence to demonstrate these observations, providing practical insights for addressing model misspecification in small area estimation (SAE).
    Release date: 2025-12-23
  • 5. Who’s asking? Interviewer effects on unit nonresponse in the Household Finance and Consumption Survey
    Articles and reports: 12-001-X202500200002
    Description: This study examines interviewer effects on household nonresponse in three waves of the Household Finance and Consumption Survey (HFCS) in Austria using a multilevel model. Addressing nonresponse at its source is crucial for maintaining survey data quality and representativeness. Our findings indicate that the variation in response behavior explained by interviewer effects decreased from about one-third in the first wave to 7% in the third wave. Effective interviewers tend to have a university degree, be married, homeowners, and have a larger workload. Additionally, higher mean wages in the household’s municipality negatively affect survey participation. These insights suggest targeted interviewer selection and training strategies to improve response rates.
    Release date: 2025-12-23
  • 6. Estimating monthly indicators for Consumer Confidence using Structural Time Series Models
    Articles and reports: 12-001-X202500200003
    Description: In this paper a model-based inference procedure based on a multivariate structural time series model is developed for the production of monthly figures about consumer confidence. The input for the model are five series of direct estimates for the indices that measure consumer confidence, which are derived from the Dutch Consumer Survey. The model improves the accuracy of the direct estimates, since it provides a better separation of measurement errors and sampling errors from estimated target parameters. The standard errors for the month-to-month changes are clearly smaller under the time series model. A second problem addressed in this paper is related to the transition to a new survey process in 2017. Structural time series models in combination with a parallel run are applied to estimate discontinuities induced by the redesign. An algorithm designed for the consumer confidence variables is developed to construct uninterrupted input series for the aforementioned structural time series model. This inference method facilitated a smooth transition to a new survey design and resulted in uninterrupted series about consumer confidence that date back to 1986. The method is implemented for the production of official monthly figures on consumer confidence in the Netherlands.
    Release date: 2025-12-23
  • 7. Collinearity diagnostics in generalized linear models fitted with survey data
    Articles and reports: 12-001-X202500200004
    Description: The class of generalized linear models (GLM) is a flexible generalization of ordinary least squares regression that allows the linear model to be related to the response variable via a link function and assumes the magnitude of the variance of each measurement to be a function of its predicted value. Multicollinearity in GLMs can inflate variances of the estimated coefficients and cause poor prediction in certain regions of the regression space. It may also cause a nonsignificant Wald statistic even when the predictors are highly predictive in a model of the family of GLMs. Little previous research has closely investigated the diagnostics of multicollinearity in GLMs, especially when complex survey data are used. In this paper, we develop variance inflation factors (VIFs) that measure the amount that the variance of a parameter estimator is increased due to multicollinearity in GLMs. We also extend VIFs and condition indexes to apply to complex survey data, accounting for design features, e.g. weights, clusters, and strata. Illustrations of these methods are given using data from a household survey of health and nutrition.
    Release date: 2025-12-23
  • 8. Quantile balancing inverse probability weighting for non-probability samples
    Articles and reports: 12-001-X202500200005
    Description: The use of non-probability data sources for statistical purposes and for official statistics has become increasingly popular in recent years. However, statistical inference based on non-probability samples is made more difficult by nature of their biasedness and lack of representativity. In this paper we propose quantile balancing inverse probability weighting estimator (QBIPW) for non-probability samples. We apply the idea of Harms and Duchesne (2006) allowing the use of quantile information in the estimation process to reproduce known totals and the distribution of auxiliary variables. We discuss the estimation of the QBIPW probabilities and its variance. Our simulation study has demonstrated that the proposed estimators are robust against model mis-specification and, as a result, help to reduce bias and mean squared error. Finally, we applied the proposed methods to estimate the share of job vacancies aimed at Ukrainian workers in Poland using an integrated set of administrative and survey data about job vacancies.
    Release date: 2025-12-23
  • 9. Quality indicators for representation in administrative data
    Articles and reports: 12-001-X202500200006
    Description: National Statistical Institutes (NSIs) are directing resources into advancing the use of administrative data in official statistics. Administrative data, however, are not developed for the purpose of producing statistics rather as a result of an event or transaction relating to administrative procedures of organizations, public administrations and government agencies. Therefore, it is essential to check the quality of the administrative data with respect to sources of error, particularly representativeness to the target population. In this paper, we utilize the strength of probability-based reference samples or censuses that can be used to detect the lack of representativeness in administrative data and introduce quality indicators based on distance metrics and representativity indicators (R-indicators). We demonstrate their application with a simulation study and discuss a real application applied on a UK Office for National Statistics (ONS) administrative dataset.
    Release date: 2025-12-23
  • 10. Integrating probability and non-probability samples through deep learning-based mass imputation
    Articles and reports: 12-001-X202500200007
    Description: Although probability samples have been regarded as the gold standard to collect information for population-based study, non-probability samples have been used frequently in practice due to low cost, convenience, and the lack of the sampling frame for the survey. Naïve estimates based on non-probability samples without any adjustments may be misleading due to selection bias. Recently, a valid data integration approach that includes mass imputation, propensity score weighting, and calibration has been used to improve the representativeness of non-probability samples. The effectiveness of the mass imputation approach depends on the underlying model assumptions. In this paper, we propose using deep learning for the mass imputation in the combining of probability and non-probability samples and compare it with several modern machine learning-based mass imputation approaches, including generalized additive modeling, regression tree, random forest, and XG-boosting. In the simulation study, deep learning-based approaches have been shown to be more robust and effective than other mass imputation approaches against the failure of underlying model assumptions under non-linearity scenarios.
    Release date: 2025-12-23
Reference (380)

Reference (380) (50 to 60 of 380 results)

  • 51. Using family-related variables from the Census of Population and the National Household Survey microdata files Archived
    Surveys and statistical programs – Documentation: 91F0015M2016012
    Description:

    This article provides information on using family-related variables from the microdata files of Canada’s Census of Population. These files exist internally at Statistics Canada, in the Research Data Centres (RDCs), and as public-use microdata files (PUMFs). This article explains certain technical aspects of all three versions, including the creation of multi-level variables for analytical purposes.

    Release date: 2016-12-22
  • 52. 2016 Census Program Content Test: Design and Results
    Notices and consultations: 92-140-X2016001
    Description:

    The 2016 Census Program Content Test was conducted from May 2 to June 30, 2014. The Test was designed to assess the impact of any proposed content changes to the 2016 Census Program and to measure the impact of including a social insurance number (SIN) question on the data quality.

    This quantitative test used a split-panel design involving 55,000 dwellings, divided into 11 panels of 5,000 dwellings each: five panels were dedicated to the Content Test while the remaining six panels were for the SIN Test. Two models of test questionnaires were developed to meet the objectives, namely a model with all the proposed changes EXCEPT the SIN question and a model with all the proposed changes INCLUDING the SIN question. A third model of 'control' questionnaire with the 2011 content was also developed. The population living in a private dwelling in mail-out areas in one of the ten provinces was targeted for the test. Paper and electronic response channels were part of the Test as well.

    This report presents the Test objectives, the design and a summary of the analysis in order to determine potential content for the 2016 Census Program. Results from the data analysis of the Test were not the only elements used to determine the content for 2016. Other elements were also considered, such as response burden, comparison over time and users’ needs.

    Release date: 2016-04-01
  • 53. The Alternative Data Solution – Experience of the Producer Prices Division Archived
    Surveys and statistical programs – Documentation: 11-522-X201700014706
    Description:

    Over the last decade, Statistics Canada’s Producer Prices Division has expanded its service producer price indexes program and continued to improve its goods and construction producer price indexes program. While the majority of price indexes are based on traditional survey methods, efforts were made to increase the use of administrative data and alternative data sources in order to reduce burden on our respondents. This paper focuses mainly on producer price programs, but also provides information on the growing importance of alternative data sources at Statistics Canada. In addition, it presents the operational challenges and risks that statistical offices could face when relying more and more on third-party outputs. Finally, it presents the tools being developed to integrate alternative data while collecting metadata.

    Release date: 2016-03-24
  • 54. Challenges and results in using Audit trail data to monitor Labour Force Survey data quality Archived
    Surveys and statistical programs – Documentation: 11-522-X201700014707
    Description:

    The Labour Force Survey (LFS) is a monthly household survey of about 56,000 households that provides information on the Canadian labour market. Audit Trail is a Blaise programming option, for surveys like LFS with Computer Assisted Interviewing (CAI), which creates files containing every keystroke and edit and timestamp of every data collection attempt on all households. Combining such a large survey with such a complete source of paradata opens the door to in-depth data quality analysis but also quickly leads to Big Data challenges. How can meaningful information be extracted from this large set of keystrokes and timestamps? How can it help assess the quality of LFS data collection? The presentation will describe some of the challenges that were encountered, solutions that were used to address them, and results of the analysis on data quality.

    Release date: 2016-03-24
  • 55. Statistics Canada’s Household Survey Frames Programme – Strategic Research Enabling a shift to increased use of Admin Data as Input to the Social statistics program Archived
    Surveys and statistical programs – Documentation: 11-522-X201700014708
    Description:

    Statistics Canada’s Household Survey Frames (HSF) Programme provides various universe files that can be used alone or in combination to improve survey design, sampling, collection, and processing in the traditional “need to contact a household model.” Even as surveys are migrating onto these core suite of products, the HSF is starting to plan the changes to infrastructure, organisation, and linkages with other data assets in Statistics Canada that will help enable a shift to increased use of a wide variety of administrative data as input to the social statistics programme. The presentation will provide an overview of the HSF Programme, foundational concepts that will need to be implemented to expand linkage potential, and will identify strategic research being under-taken toward 2021.

    Release date: 2016-03-24
  • 56. The Data Warehouse and analytical tools to facilitate the integration of the Canadian Macroeconomic Accounts Archived
    Surveys and statistical programs – Documentation: 11-522-X201700014710
    Description:

    The Data Warehouse has modernized the way the Canadian System of Macroeconomic Accounts (MEA) are produced and analyzed today. Its continuing evolution facilitates the amounts and types of analytical work that is done within the MEA. It brings in the needed element of harmonization and confrontation as the macroeconomic accounts move toward full integration. The improvements in quality, transparency, and timeliness have strengthened the statistics that are being disseminated.

    Release date: 2016-03-24
  • 57. Comparing Survey Data to Administrative Sources: Immigration, Labour, and Demographic data from the Longitudinal and International Study of Adults Archived
    Surveys and statistical programs – Documentation: 11-522-X201700014716
    Description:

    Administrative data, depending on its source and original purpose, can be considered a more reliable source of information than survey-collected data. It does not require a respondent to be present and understand question wording, and it is not limited by the respondent’s ability to recall events retrospectively. This paper compares selected survey data, such as demographic variables, from the Longitudinal and International Study of Adults (LISA) to various administrative sources for which LISA has linkage agreements in place. The agreement between data sources, and some factors that might affect it, are analyzed for various aspects of the survey.

    Release date: 2016-03-24
  • 58. Student Pathways and Graduate Outcomes Archived
    Surveys and statistical programs – Documentation: 11-522-X201700014717
    Description:

    Files with linked data from the Statistics Canada, Postsecondary Student Information System (PSIS) and tax data can be used to examine the trajectories of students who pursue postsecondary education (PSE) programs and their post-schooling labour market outcomes. On one hand, administrative data on students linked longitudinally can provide aggregate information on student pathways during postsecondary studies such as persistence rates, graduation rates, mobility, etc. On the other hand, the tax data could supplement the PSIS data to provide information on employment outcomes such as average and median earnings or earnings progress by employment sector (industry), field of study, education level and/or other demographic information, year over year after graduation. Two longitudinal pilot studies have been done using administrative data on postsecondary students of Maritimes institutions which have been longitudinally linked and linked to Statistics Canada Ttx data (the T1 Family File) for relevant years. This article first focuses on the quality of information in the administrative data and the methodology used to conduct these longitudinal studies and derive indicators. Second, it will focus on some limitations when using administrative data, rather than a survey, to define some concepts.

    Release date: 2016-03-24
  • 59. 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
  • 60. 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

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  • 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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