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All (175) (0 to 10 of 175 results)

  • 1. Memory disabilities, 2022
    Stats in brief: 11-627-M2024044
    Description: Utilizing data from the 2022 Canadian Survey on Disability, this infographic highlights the trends and experiences of persons with memory disabilities. This release is part of a series of infographics that focus on specific disability types.
    Release date: 2024-10-08
  • 2. Small Area Estimation Methodology Using Labour Force Survey Data
    Articles and reports: 75-005-M2024003
    Description: This document briefly describes the small area estimation methodology developed to produce monthly estimates of employment and unemployment rate for census metropolitan areas, census agglomerations, and self-contained labour areas using data from the Labour Force Survey, Employment Insurance statistics and population projections.
    Release date: 2024-09-17
  • 3. Canadian labour force: What will happen once baby boomers retire?
    Articles and reports: 75-006-X202400100005
    Description: This study uses various demographic scenarios to examine the effects of different immigration levels and labour force participation rates on the size and composition of the Canadian labour force to 2041. These scenarios take into account the targets of the 2024–2026 Immigration Levels Plan, published in November 2023 by Immigration, Refugees and Citizenship Canada, as well as recent demographic developments, such as those related to the COVID-19 pandemic and the increase in the number of permanent and temporary immigrants admitted to Canada in 2022 and 2023.
    Release date: 2024-08-06
  • 4. Short-term rentals in the Canadian housing market
    Stats in brief: 11-621-M2024010
    Description: The paper focuses on the subset of short-term rentals (STRs) that could potentially serve as long-term housing. This subset of STRs, referred to as potential long-term dwellings (PLTDs), is intended to capture STR units that are not serving as anyone’s primary residence, but could potentially function as long-term housing (either as owner-occupied or rental units). The PLTD subset is compared with total housing units (owned or rented) at the national, provincial and territorial levels, as well as in major census metropolitan areas and in tourist areas.
    Release date: 2024-07-30
  • 5. The role of short-term rentals in the Canadian housing market
    Stats in brief: 11-627-M2024032
    Description: This infographic is a visual representation of short-term rental (STR) activity across Canada, focusing particularly on the subset of STRs that could potentially be used for long-term housing. This subset of STRs is referred to as potential long-term dwellings (PLTDs), it comprises entire units listed for more than 180 days a year, excluding vacation-type properties.
    Release date: 2024-07-30
  • 6. Gender diversity of Canadian postsecondary students, 2021/2022
    Stats in brief: 11-627-M2024026
    Description: Using data from the Postsecondary Student Information System (PSIS) and the Census of Population, 2021, this infographic provides information on enrolment in Canadian public postsecondary institutions for transgender and non-binary people.
    Release date: 2024-06-25
  • 7. Labour market characteristics of persons with and without disabilities, 2023
    Articles and reports: 71-222-X2024002
    Description: This article examines trends in rates of employment and unemployment, as well as hourly wages and work hours, for the year 2023, and explores how disability intersects with age, sex, educational attainment, and racialized groups to influence labour market outcomes.
    Release date: 2024-06-13
  • 8. Modelling intra-annual measurement in linked administrative and survey data Archived
    Articles and reports: 11-522-X202200100012
    Description: At Statistics Netherlands (SN) for some economic sectors two partly-independent intra-annual turnover index series are available: a monthly series based on survey data and a quarterly series based on value added tax data for the smaller units and re-used survey data for the other units. SN aims to benchmark the monthly turnover index series to the quarterly census data on a quarterly basis. This cannot currently be done because the tax data has a different quarterly pattern: the turnover is relatively large in the fourth quarter of the year and smaller in the first quarter. With the current study we aim to describe this deviating quarterly pattern at micro level. In the past we developed a mixture model using absolute turnover levels that could explain part of the quarterly patterns. Because the absolute turnover levels differ between the two series, in the current study we use a model based on relative quarterly turnover levels within a year.
    Release date: 2024-03-25
  • 9. A method for estimating the effect of classification errors on statistics for two domains
    Articles and reports: 12-001-X202300200002
    Description: Being able to quantify the accuracy (bias, variance) of published output is crucial in official statistics. Output in official statistics is nearly always divided into subpopulations according to some classification variable, such as mean income by categories of educational level. Such output is also referred to as domain statistics. In the current paper, we limit ourselves to binary classification variables. In practice, misclassifications occur and these contribute to the bias and variance of domain statistics. Existing analytical and numerical methods to estimate this effect have two disadvantages. The first disadvantage is that they require that the misclassification probabilities are known beforehand and the second is that the bias and variance estimates are biased themselves. In the current paper we present a new method, a Gaussian mixture model estimated by an Expectation-Maximisation (EM) algorithm combined with a bootstrap, referred to as the EM bootstrap method. This new method does not require that the misclassification probabilities are known beforehand, although it is more efficient when a small audit sample is used that yields a starting value for the misclassification probabilities in the EM algorithm. We compared the performance of the new method with currently available numerical methods: the bootstrap method and the SIMEX method. Previous research has shown that for non-linear parameters the bootstrap outperforms the analytical expressions. For nearly all conditions tested, the bias and variance estimates that are obtained by the EM bootstrap method are closer to their true values than those obtained by the bootstrap and SIMEX methods. We end this paper by discussing the results and possible future extensions of the method.
    Release date: 2024-01-03
  • 10. Official Statistics based on the Dutch Health Survey during the Covid-19 Pandemic
    Articles and reports: 12-001-X202300100004
    Description: The Dutch Health Survey (DHS), conducted by Statistics Netherlands, is designed to produce reliable direct estimates at an annual frequency. Data collection is based on a combination of web interviewing and face-to-face interviewing. Due to lockdown measures during the Covid-19 pandemic there was no or less face-to-face interviewing possible, which resulted in a sudden change in measurement and selection effects in the survey outcomes. Furthermore, the production of annual data about the effect of Covid-19 on health-related themes with a delay of about one year compromises the relevance of the survey. The sample size of the DHS does not allow the production of figures for shorter reference periods. Both issues are solved by developing a bivariate structural time series model (STM) to estimate quarterly figures for eight key health indicators. This model combines two series of direct estimates, a series based on complete response and a series based on web response only and provides model-based predictions for the indicators that are corrected for the loss of face-to-face interviews during the lockdown periods. The model is also used as a form of small area estimation and borrows sample information observed in previous reference periods. In this way timely and relevant statistics describing the effects of the corona crisis on the development of Dutch health are published. In this paper the method based on the bivariate STM is compared with two alternative methods. The first one uses a univariate STM where no correction for the lack of face-to-face observation is applied to the estimates. The second one uses a univariate STM that also contains an intervention variable that models the effect of the loss of face-to-face response during the lockdown.
    Release date: 2023-06-30
Stats in brief (13)

Stats in brief (13) (0 to 10 of 13 results)

  • 1. Memory disabilities, 2022
    Stats in brief: 11-627-M2024044
    Description: Utilizing data from the 2022 Canadian Survey on Disability, this infographic highlights the trends and experiences of persons with memory disabilities. This release is part of a series of infographics that focus on specific disability types.
    Release date: 2024-10-08
  • 2. Short-term rentals in the Canadian housing market
    Stats in brief: 11-621-M2024010
    Description: The paper focuses on the subset of short-term rentals (STRs) that could potentially serve as long-term housing. This subset of STRs, referred to as potential long-term dwellings (PLTDs), is intended to capture STR units that are not serving as anyone’s primary residence, but could potentially function as long-term housing (either as owner-occupied or rental units). The PLTD subset is compared with total housing units (owned or rented) at the national, provincial and territorial levels, as well as in major census metropolitan areas and in tourist areas.
    Release date: 2024-07-30
  • 3. The role of short-term rentals in the Canadian housing market
    Stats in brief: 11-627-M2024032
    Description: This infographic is a visual representation of short-term rental (STR) activity across Canada, focusing particularly on the subset of STRs that could potentially be used for long-term housing. This subset of STRs is referred to as potential long-term dwellings (PLTDs), it comprises entire units listed for more than 180 days a year, excluding vacation-type properties.
    Release date: 2024-07-30
  • 4. Gender diversity of Canadian postsecondary students, 2021/2022
    Stats in brief: 11-627-M2024026
    Description: Using data from the Postsecondary Student Information System (PSIS) and the Census of Population, 2021, this infographic provides information on enrolment in Canadian public postsecondary institutions for transgender and non-binary people.
    Release date: 2024-06-25
  • 5. Students in private postsecondary education, 2020: Results of a feasibility study
    Stats in brief: 11-627-M2023031
    Description: Statistics Canada, using the data collected for the Postsecondary Student Information System (PSIS), has long published education indicators for Canadian public postsecondary institutions. Data on private postsecondary institutions have not been explored at the same depth and breadth by Statistics Canada. This infographic attempts to address this data gap through the Education and Labour Market Longitudinal Platform (ELMLP) with results from the study of the T2202 Tuition and Enrolment Certificate as a new source of data.
    Release date: 2023-06-06
  • 6. Climate change statistics at Statistics Canada
    Stats in brief: 11-627-M2023025
    Description: This infographic features climate change-related data from various survey programs, from 2019 to 2022.
    Release date: 2023-05-16
  • 7. Unravelling the story about household textile and e-waste disposal in Canada Archived
    Stats in brief: 11-627-M2022015
    Description:

    This infographic visually presents information on household disposal methods of textile and e-waste for the years 2017 and 2019. It also presents total household textile and e-waste diverted from landfills or incinerators and total household waste sent to landfills and incinerators for the year 2018. This infographic is based on data from the 2017 and 2019 cycles of the Households and Environment Survey and the 2018 Waste Management Industry Survey.

    Release date: 2022-02-15
  • 8. Stats are on the menu! Canada’s restaurant industry Archived
    Stats in brief: 11-627-M2021025
    Description:

    This infographic highlights a selection of statistics on restaurants, bars and caterers in Canada.

    Release date: 2021-03-25
  • 9. The resilience and strength of the new housing market during the pandemic Archived
    Stats in brief: 45-28-0001202000100080
    Description:

    This article examines changes in new home prices in Canada for the 27 surveyed census metropolitan areas (CMAs) captured in the New Housing Price Index and compares the ranking of cities based on prices six months into the pandemic (August compared to February).

    Release date: 2020-10-05
  • 10. Retail e-commerce and COVID-19: How online shopping opened doors while many were closing Archived
    Stats in brief: 45-28-0001202000100064
    Description:

    The COVID-19 pandemic triggered decisions at all levels of government to try and minimize its spread, including shutting down non-essential retail establishments. This led to an abrupt shift in the Canadian retail environment, to which many industries had to adapt. This paper examines the impact of COVID-19 on retail e-commerce as a method of doing business during the first months of the pandemic.

    Release date: 2020-07-24
Articles and reports (162)

Articles and reports (162) (0 to 10 of 162 results)

  • 1. Small Area Estimation Methodology Using Labour Force Survey Data
    Articles and reports: 75-005-M2024003
    Description: This document briefly describes the small area estimation methodology developed to produce monthly estimates of employment and unemployment rate for census metropolitan areas, census agglomerations, and self-contained labour areas using data from the Labour Force Survey, Employment Insurance statistics and population projections.
    Release date: 2024-09-17
  • 2. Canadian labour force: What will happen once baby boomers retire?
    Articles and reports: 75-006-X202400100005
    Description: This study uses various demographic scenarios to examine the effects of different immigration levels and labour force participation rates on the size and composition of the Canadian labour force to 2041. These scenarios take into account the targets of the 2024–2026 Immigration Levels Plan, published in November 2023 by Immigration, Refugees and Citizenship Canada, as well as recent demographic developments, such as those related to the COVID-19 pandemic and the increase in the number of permanent and temporary immigrants admitted to Canada in 2022 and 2023.
    Release date: 2024-08-06
  • 3. Labour market characteristics of persons with and without disabilities, 2023
    Articles and reports: 71-222-X2024002
    Description: This article examines trends in rates of employment and unemployment, as well as hourly wages and work hours, for the year 2023, and explores how disability intersects with age, sex, educational attainment, and racialized groups to influence labour market outcomes.
    Release date: 2024-06-13
  • 4. Modelling intra-annual measurement in linked administrative and survey data Archived
    Articles and reports: 11-522-X202200100012
    Description: At Statistics Netherlands (SN) for some economic sectors two partly-independent intra-annual turnover index series are available: a monthly series based on survey data and a quarterly series based on value added tax data for the smaller units and re-used survey data for the other units. SN aims to benchmark the monthly turnover index series to the quarterly census data on a quarterly basis. This cannot currently be done because the tax data has a different quarterly pattern: the turnover is relatively large in the fourth quarter of the year and smaller in the first quarter. With the current study we aim to describe this deviating quarterly pattern at micro level. In the past we developed a mixture model using absolute turnover levels that could explain part of the quarterly patterns. Because the absolute turnover levels differ between the two series, in the current study we use a model based on relative quarterly turnover levels within a year.
    Release date: 2024-03-25
  • 5. A method for estimating the effect of classification errors on statistics for two domains
    Articles and reports: 12-001-X202300200002
    Description: Being able to quantify the accuracy (bias, variance) of published output is crucial in official statistics. Output in official statistics is nearly always divided into subpopulations according to some classification variable, such as mean income by categories of educational level. Such output is also referred to as domain statistics. In the current paper, we limit ourselves to binary classification variables. In practice, misclassifications occur and these contribute to the bias and variance of domain statistics. Existing analytical and numerical methods to estimate this effect have two disadvantages. The first disadvantage is that they require that the misclassification probabilities are known beforehand and the second is that the bias and variance estimates are biased themselves. In the current paper we present a new method, a Gaussian mixture model estimated by an Expectation-Maximisation (EM) algorithm combined with a bootstrap, referred to as the EM bootstrap method. This new method does not require that the misclassification probabilities are known beforehand, although it is more efficient when a small audit sample is used that yields a starting value for the misclassification probabilities in the EM algorithm. We compared the performance of the new method with currently available numerical methods: the bootstrap method and the SIMEX method. Previous research has shown that for non-linear parameters the bootstrap outperforms the analytical expressions. For nearly all conditions tested, the bias and variance estimates that are obtained by the EM bootstrap method are closer to their true values than those obtained by the bootstrap and SIMEX methods. We end this paper by discussing the results and possible future extensions of the method.
    Release date: 2024-01-03
  • 6. Official Statistics based on the Dutch Health Survey during the Covid-19 Pandemic
    Articles and reports: 12-001-X202300100004
    Description: The Dutch Health Survey (DHS), conducted by Statistics Netherlands, is designed to produce reliable direct estimates at an annual frequency. Data collection is based on a combination of web interviewing and face-to-face interviewing. Due to lockdown measures during the Covid-19 pandemic there was no or less face-to-face interviewing possible, which resulted in a sudden change in measurement and selection effects in the survey outcomes. Furthermore, the production of annual data about the effect of Covid-19 on health-related themes with a delay of about one year compromises the relevance of the survey. The sample size of the DHS does not allow the production of figures for shorter reference periods. Both issues are solved by developing a bivariate structural time series model (STM) to estimate quarterly figures for eight key health indicators. This model combines two series of direct estimates, a series based on complete response and a series based on web response only and provides model-based predictions for the indicators that are corrected for the loss of face-to-face interviews during the lockdown periods. The model is also used as a form of small area estimation and borrows sample information observed in previous reference periods. In this way timely and relevant statistics describing the effects of the corona crisis on the development of Dutch health are published. In this paper the method based on the bivariate STM is compared with two alternative methods. The first one uses a univariate STM where no correction for the lack of face-to-face observation is applied to the estimates. The second one uses a univariate STM that also contains an intervention variable that models the effect of the loss of face-to-face response during the lockdown.
    Release date: 2023-06-30
  • 7. The growing share of private short-term rental revenue in the Canadian accommodation services subsector: Trends from 2017 to 2021
    Articles and reports: 11-621-M2023008
    Description: This is an overview of how private short-term rentals have grown and impacted the accommodation services subsector from 2017 to 2021. It includes a discussion of national, provincial, territorial and selected subprovincial trends and what changed during the COVID-19 pandemic years. This study examined results from Statistics Canada's annual accommodation services survey and AirDNA's monthly data on short-term rentals to make market share comparisons at various geographic levels.
    Release date: 2023-06-30
  • 8. Students in private postsecondary education, 2020: A feasibility study
    Articles and reports: 37-20-00012023005
    Description: This methodological document accompanies the infographic entitled “Students in private postsecondary education, 2020: Results of a feasibility study”. It describes the methodology and data limitations for the integration of the T2202 Tuition and Enrolment Certificate with the Census 2021 for the infographic. It also explores the coherence of the results across different data sources, namely the Postsecondary Student Information System (PSIS) and T1 Family File (T1FF), to validate the results. The data integration was possible due to the Education and Labour Market Longitudinal Platform (ELMLP).
    Release date: 2023-06-06
  • 9. Postsecondary students receiving payments from the Canada Emergency Response Benefit (CERB) and the Canada Emergency Student Benefit (CESB) in 2020
    Articles and reports: 81-595-M2023001
    Description: This paper uses longitudinal data derived from a database that integrates data from the Postsecondary Student Information System (PSIS) with data from the Canada Emergency Response Benefit (CERB) and the Canada Emergency Student Benefit (CESB) to provide insights into the differences in the rate of receipt of CERB and CESB of students who were in postsecondary education at the beginning of the COVID-19 pandemic. The emergency benefits payments are examined along various educational and socio-economic characteristics.
    Release date: 2023-01-16
  • 10. Multilevel time series modelling of antenatal care coverage in Bangladesh at disaggregated administrative levels
    Articles and reports: 12-001-X202200200010
    Description:

    Multilevel time series (MTS) models are applied to estimate trends in time series of antenatal care coverage at several administrative levels in Bangladesh, based on repeated editions of the Bangladesh Demographic and Health Survey (BDHS) within the period 1994-2014. MTS models are expressed in an hierarchical Bayesian framework and fitted using Markov Chain Monte Carlo simulations. The models account for varying time lags of three or four years between the editions of the BDHS and provide predictions for the intervening years as well. It is proposed to apply cross-sectional Fay-Herriot models to the survey years separately at district level, which is the most detailed regional level. Time series of these small domain predictions at the district level and their variance-covariance matrices are used as input series for the MTS models. Spatial correlations among districts, random intercept and slope at the district level, and different trend models at district level and higher regional levels are examined in the MTS models to borrow strength over time and space. Trend estimates at district level are obtained directly from the model outputs, while trend estimates at higher regional and national levels are obtained by aggregation of the district level predictions, resulting in a numerically consistent set of trend estimates.

    Release date: 2022-12-15
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