Analysis

COVID-19 A data perspective

COVID-19: A data perspective: Explore key economic trends and social challenges that arise as the COVID-19 situation evolves.

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  • Stats in brief: 11-001-X202201416361
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2022-01-14

  • Stats in brief: 11-001-X202201423503
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2022-01-14

  • Stats in brief: 11-627-M2021004
    Description:

    This infographic presents differences in the caregiving arrangements of Canadians, as captured in Wave 4 (2018) of the Longitudinal and International Study of Adults. Among individuals who acted as caregivers between January 2016 and December 2017, some had provided care each month over the two-year period, while others had provided care for a continuous but shorter period of time, or on and off over the period considered. Moreover, individuals in different arrangements varied in their characteristics and in the intensity of the care they had provided.

    Release date: 2022-01-14

  • Stats in brief: 11-627-M2021074
    Description:

    The 2018 General Social Survey on Caregiving and Care Receiving collects information on Canadians who provide care to family and friends with a long-term health condition, disability or problems related to aging. The survey also covers individuals who receive this care and about the challenges both groups face.

    Taking on the responsibility of an informal caregiver often means balancing other competing demands of life, such as working at a paid job, raising children and maintaining healthy interpersonal relationships. This infographic explores how the number of hours per week spent on caregiving activities effects the overall well-being of informal caregivers and their participation in daily and social activities.

    Release date: 2022-01-14

  • Journals and periodicals: 11-627-M
    Description:

    Every year, Statistics Canada collects data from hundreds of surveys. As the amount of data gathered increases, Statistics Canada has introduced infographics to help people, business owners, academics, and management at all levels, understand key information derived from the data. Infographics can be used to quickly communicate a message, to simplify the presentation of large amounts of data, to see data patterns and relationships, and to monitor changes in variables over time.

    These infographics will provide a quick overview of Statistics Canada survey data.

    Release date: 2022-01-14

  • Stats in brief: 11-001-X202201319277
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2022-01-13

  • Stats in brief: 11-001-X202201332584
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2022-01-13

  • Journals and periodicals: 91-214-X
    Description:

    This publication presents annual estimates of population for subprovincial areas of Canada, such as census metropolitan areas (CMAs), census agglomerations (CAs), economic regions (ERs) and census divisions (CDs). The following components of population change are also presented: births, deaths, immigration, emigration, returning emigration, net temporary emigration, net non-permanent residents and interprovincial and intraprovincial migration. The estimates are based on the most recent census of population results available at the time of publication, which have been adjusted for census net undercoverage (including adjustment for incompletely enumerated Indian reserves). This publication also contains highlights and an analysis of the most recent demographic trends, as well as a description of the concepts, methods and data quality of the estimates.

    Release date: 2022-01-13

  • Stats in brief: 45-28-0001
    Description:

    A series of articles on various subjects which explore the impact of COVID-19 on the socio-economic landscape. New articles will be released periodically.

    Release date: 2022-01-12

  • Stats in brief: 45-28-0001202200100001
    Description:

    This article examines some of the effects of COVID-19 on rural businesses in Canada, with comparison to urban counterparts by industry for contextual support. Topics include business obstacles, expectations for the next year, workforce changes and other subjects from the Canadian Survey on Business Conditions, fourth quarter of 2021.

    Release date: 2022-01-12
Stats in brief (2,167)

Stats in brief (2,167) (40 to 50 of 2,167 results)

Articles and reports (6,261)

Articles and reports (6,261) (0 to 10 of 6,261 results)

  • Articles and reports: 11-621-M2022001
    Description:

    Despite the third wave of the pandemic, the trend observed is generally positive in the first half of 2021 for several service industries. Using administrative datasets, such as the goods and services tax (GST) data, this analysis explores the impacts of the pandemic, resiliency and adaptation of a selected group of service industries by comparing GST revenue from the first half of 2021 relative to the same period in 2020.

    Release date: 2022-01-12

  • Articles and reports: 75F0002M2021009
    Description:

    This paper outlines two indicators, food insecurity and unmet health needs, identified in Government of Canada's Opportunity for All - Canada's First Poverty Reduction Strategy that can now be produced using the Canadian Income Survey (CIS), starting in reference year 2018. Specifically, the paper describes the two indicators, provides estimates for the 2018 and 2019 reference years and compares the CIS derived estimates to similar estimates produced by the Canadian Community Health Survey.

    Release date: 2022-01-07

  • Articles and reports: 12-001-X202100200001
    Description:

    The Fay-Herriot model is often used to produce small area estimates. These estimates are generally more efficient than standard direct estimates. In order to evaluate the efficiency gains obtained by small area estimation methods, model mean square error estimates are usually produced. However, these estimates do not reflect all the peculiarities of a given domain (or area) because model mean square errors integrate out the local effects. An alternative is to estimate the design mean square error of small area estimators, which is often more attractive from a user point of view. However, it is known that design mean square error estimates can be very unstable, especially for domains with few sampled units. In this paper, we propose two local diagnostics that aim to choose between the empirical best predictor and the direct estimator for a particular domain. We first find an interval for the local effect such that the best predictor is more efficient under the design than the direct estimator. Then, we consider two different approaches to assess whether it is plausible that the local effect falls in this interval. We evaluate our diagnostics using a simulation study. Our preliminary results indicate that our diagnostics are effective for choosing between the empirical best predictor and the direct estimator.

    Release date: 2022-01-06

  • Articles and reports: 12-001-X202100200002
    Description:

    When linking massive data sets, blocking is used to select a manageable subset of record pairs at the expense of losing a few matched pairs. This loss is an important component of the overall linkage error, because blocking decisions are made early on in the linkage process, with no way to revise them in subsequent steps. Yet, measuring this contribution is still a major challenge because of the need to model all the pairs in the Cartesian product of the sources, not just those satisfying the blocking criteria. Unfortunately, previous error models are of little use because they typically do not meet this requirement. This paper addresses the issue with a new finite mixture model, which dispenses with clerical reviews, training data, or the assumption that the linkage variables are conditionally independent. It applies when applying a standard blocking procedure for the linkage of a file to a register or a census with complete coverage, where both sources are free of duplicate records.

    Release date: 2022-01-06

  • Articles and reports: 12-001-X202100200003
    Description:

    Calibration weighting is a statistically efficient way for handling unit nonresponse. Assuming the response (or output) model justifying the calibration-weight adjustment is correct, it is often possible to measure the variance of estimates in an asymptotically unbiased manner. One approach to variance estimation is to create jackknife replicate weights. Sometimes, however, the conventional method for computing jackknife replicate weights for calibrated analysis weights fails. In that case, an alternative method for computing jackknife replicate weights is usually available. That method is described here and then applied to a simple example.

    Release date: 2022-01-06

  • Articles and reports: 12-001-X202100200004
    Description:

    This note presents a comparative study of three methods for constructing confidence intervals for the mean and quantiles based on survey data with nonresponse. These methods, empirical likelihood, linearization, and that of Woodruff’s (1952), were applied to data on income obtained from the 2015 Mexican Intercensal Survey, and to simulated data. A response propensity model was used for adjusting the sampling weights, and the empirical performance of the methods was assessed in terms of the coverage of the confidence intervals through simulation studies. The empirical likelihood and linearization methods had a good performance for the mean, except when the variable of interest had some extreme values. For quantiles, the linearization method had a poor performance, while the empirical likelihood and Woodruff methods had a better one, though without reaching the nominal coverage when the variable of interest had values with high frequency near the quantile of interest.

    Release date: 2022-01-06

  • Articles and reports: 12-001-X202100200005
    Description:

    Variance estimation is a challenging problem in surveys because there are several nontrivial factors contributing to the total survey error, including sampling and unit non-response. Initially devised to capture the variance of non-trivial statistics based on independent and identically distributed data, the bootstrap method has since been adapted in various ways to address survey-specific elements/factors. In this paper we look into one of those variants, the with-replacement bootstrap. We consider household surveys, with or without sub-sampling of individuals. We make explicit the benchmark variance estimators that the with-replacement bootstrap aims at reproducing. We explain how the bootstrap can be used to account for the impact sampling, treatment of non-response and calibration have on total survey error. For clarity, the proposed methods are illustrated on a running example. They are evaluated through a simulation study, and applied to a French Panel for Urban Policy. Two SAS macros to perform the bootstrap methods are also developed.

    Release date: 2022-01-06

  • Articles and reports: 12-001-X202100200006
    Description:

    Sample-based calibration occurs when the weights of a survey are calibrated to control totals that are random, instead of representing fixed population-level totals. Control totals may be estimated from different phases of the same survey or from another survey. Under sample-based calibration, valid variance estimation requires that the error contribution due to estimating the control totals be accounted for. We propose a new variance estimation method that directly uses the replicate weights from two surveys, one survey being used to provide control totals for calibration of the other survey weights. No restrictions are set on the nature of the two replication methods and no variance-covariance estimates need to be computed, making the proposed method straightforward to implement in practice. A general description of the method for surveys with two arbitrary replication methods with different numbers of replicates is provided. It is shown that the resulting variance estimator is consistent for the asymptotic variance of the calibrated estimator, when calibration is done using regression estimation or raking. The method is illustrated in a real-world application, in which the demographic composition of two surveys needs to be harmonized to improve the comparability of the survey estimates.

    Release date: 2022-01-06

  • Articles and reports: 12-001-X202100200007
    Description:

    In this paper, we consider the Fay-Herriot model for small area estimation. In particular, we are interested in the impact of sampling variance smoothing and modeling on the model-based estimates. We present methods of smoothing and modeling for the sampling variances and apply the proposed models to a real data analysis. Our results indicate that sampling variance smoothing can improve the efficiency and accuracy of the model-based estimator. For sampling variance modeling, the HB models of You (2016) and Sugasawa, Tamae and Kubokawa (2017) perform equally well to improve the direct survey estimates.

    Release date: 2022-01-06

  • Articles and reports: 12-001-X202100200008
    Description:

    Multiple-frame surveys, in which independent probability samples are selected from each of Q sampling frames, have long been used to improve coverage, to reduce costs, or to increase sample sizes for subpopulations of interest. Much of the theory has been developed assuming that (1) the union of the frames covers the population of interest, (2) a full-response probability sample is selected from each frame, (3) the variables of interest are measured in each sample with no measurement error, and (4) sufficient information exists to account for frame overlap when computing estimates. After reviewing design, estimation, and calibration for traditional multiple-frame surveys, I consider modifications of the assumptions that allow a multiple-frame structure to serve as an organizing principle for other data combination methods such as mass imputation, sample matching, small area estimation, and capture-recapture estimation. Finally, I discuss how results from multiple-frame survey research can be used when designing and evaluating data collection systems that integrate multiple sources of data.

    Release date: 2022-01-06
Journals and periodicals (317)

Journals and periodicals (317) (0 to 10 of 317 results)

  • Journals and periodicals: 11-627-M
    Description:

    Every year, Statistics Canada collects data from hundreds of surveys. As the amount of data gathered increases, Statistics Canada has introduced infographics to help people, business owners, academics, and management at all levels, understand key information derived from the data. Infographics can be used to quickly communicate a message, to simplify the presentation of large amounts of data, to see data patterns and relationships, and to monitor changes in variables over time.

    These infographics will provide a quick overview of Statistics Canada survey data.

    Release date: 2022-01-14

  • Journals and periodicals: 91-214-X
    Description:

    This publication presents annual estimates of population for subprovincial areas of Canada, such as census metropolitan areas (CMAs), census agglomerations (CAs), economic regions (ERs) and census divisions (CDs). The following components of population change are also presented: births, deaths, immigration, emigration, returning emigration, net temporary emigration, net non-permanent residents and interprovincial and intraprovincial migration. The estimates are based on the most recent census of population results available at the time of publication, which have been adjusted for census net undercoverage (including adjustment for incompletely enumerated Indian reserves). This publication also contains highlights and an analysis of the most recent demographic trends, as well as a description of the concepts, methods and data quality of the estimates.

    Release date: 2022-01-13

  • Journals and periodicals: 11-621-M
    Geography: Canada
    Description:

    The papers published in the Analysis in Brief analytical series shed light on current economic issues. Aimed at a general audience, they cover a wide range of topics including National Accounts, business enterprises, trade, transportation, agriculture, the environment, manufacturing, science and technology, services, etc.

    Release date: 2022-01-12

  • Journals and periodicals: 75F0002M
    Description:

    This series provides detailed documentation on income developments, including survey design issues, data quality evaluation and exploratory research.

    Release date: 2022-01-07

  • Journals and periodicals: 12-001-X
    Geography: Canada
    Description:

    The journal publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves.

    Release date: 2022-01-06

  • Journals and periodicals: 46-28-0001
    Description:

    This publication provides insights on housing data and analysis at Statistics Canada. Readers can access in-depth information on the latest housing data released by the Agency. The series relies on both descriptive and analytical methods to analyze administrative and survey data sets that relate to housing.

    Release date: 2022-01-06

  • Journals and periodicals: 11-631-X
    Description:

    Statistics Canada engages regularly with Canadians to discuss statistical findings about the country’s economy, society and environment. Events are held in various cities throughout the year to discuss the use of statistics in many fields. These events provide Statistics Canada with an opportunity to promote the role of official statistics and better understand data users’ needs.

    This series provides online access to the presentations that were made at outreach events with data users.

    Release date: 2021-12-22

  • 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: 2021-12-09

  • Journals and periodicals: 89-654-X
    Description:

    The Canadian Survey on Disability (CSD) is a national survey of Canadians aged 15 and over whose everyday activities are limited because of a long-term condition or health-related problem.

    Release date: 2021-12-01

  • Journals and periodicals: 85-002-X
    Geography: Canada
    Description:

    This publication provides in-depth analysis and detailed statistics on a variety of topics and issues related to justice and public safety. Topics include crime, victimization, homicide, civil, family and criminal courts, and correctional services. Issues related to community safety, and perceptions of safety are also covered. The publication is intended for those with an interest in Canada's justice and public safety systems as well as those who plan, establish, administer and evaluate programs and projects related to justice and public safety.

    Release date: 2021-11-25
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