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All (168)

All (168) (0 to 10 of 168 results)

1. 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
2. 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
3. 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
4. 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
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. 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
7. 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
8. 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
9. 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
10. Persistence and graduation indicators of postsecondary students by parental income, 2012/2013 entry cohort
Articles and reports: 81-595-M2022005
Description:
This fact sheet uses longitudinal data combining information from the Postsecondary Student Information System (PSIS) with data from the T1 Family File (T1FF) to explore the association between parental income and the pathways of young adults in postsecondary education for new students in the 2012/2013 academic year.

Release date: 2022-07-19

Stats in brief (9)

Stats in brief (9) ((9 results))

1. 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
2. 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
3. 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
4. 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
5. 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
6. 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
7. Price trends and outlook in key Canadian housing markets Archived
Stats in brief: 45-28-0001202000100053
Description:
This article examines key housing markets in Canada prior to COVID-19 and offers an outlook of the impacts of the pandemic on the real estate market over the next few months. Price trends for four property types, such as new houses, new condominiums, resale houses and resale condominiums are explored. Prior to COVID-19, the price of condominium apartments increased at a faster pace than singles, semi-detached and row homes. The global pandemic may cause a shift of preferences for larger homes instead of condominiums as future home buyers may prefer larger homes in the suburbs as working from home becomes more prevalent.
Release date: 2020-07-21
8. The Impact of COVID-19 on Key Housing Markets Archived
Stats in brief: 11-627-M2020050
Description:
This infographic examines key housing markets in Canada prior to COVID-19 and offers an outlook of the impacts of the pandemic on the real estate market over the next few months. Price trends for four property types, such as new houses, new condominiums, resale houses and resale condominiums are explored. Prior to COVID-19, the price of condominium apartments increased at a faster pace than single, semi-detached and row homes. Since the beginning of the pandemic, many changes have been impacting the real estate industry, from virtual tours to a change in preference towards larger homes in the suburb. We offer an outlook of the impact of those new realities on the real estate market going forward.
Release date: 2020-07-21
9. Money laundering in Canada, 2009 Archived
Stats in brief: 85-005-X201100111454
Geography: Canada
Description:
This Juristat Bulletin presents the most up-to-date information on police-reported incidents and court cases involving money laundering in Canada. Specific issues include: rates of money laundering, characteristics of accused, such as age and sex, and the sentences most often received for incidents of money laundering.
Release date: 2011-06-21

Articles and reports (159)

Articles and reports (159) (0 to 10 of 159 results)

1. 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
2. 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
3. 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
4. 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
5. 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
6. 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
7. 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
8. Persistence and graduation indicators of postsecondary students by parental income, 2012/2013 entry cohort
Articles and reports: 81-595-M2022005
Description:
This fact sheet uses longitudinal data combining information from the Postsecondary Student Information System (PSIS) with data from the T1 Family File (T1FF) to explore the association between parental income and the pathways of young adults in postsecondary education for new students in the 2012/2013 academic year.

Release date: 2022-07-19
9. Using Multiple Imputation of Latent Classes to construct population census tables with data from multiple sources
Articles and reports: 12-001-X202200100008
Description:
The Multiple Imputation of Latent Classes (MILC) method combines multiple imputation and latent class analysis to correct for misclassification in combined datasets. Furthermore, MILC generates a multiply imputed dataset which can be used to estimate different statistics in a straightforward manner, ensuring that uncertainty due to misclassification is incorporated when estimating the total variance. In this paper, it is investigated how the MILC method can be adjusted to be applied for census purposes. More specifically, it is investigated how the MILC method deals with a finite and complete population register, how the MILC method can simultaneously correct misclassification in multiple latent variables and how multiple edit restrictions can be incorporated. A simulation study shows that the MILC method is in general able to reproduce cell frequencies in both low- and high-dimensional tables with low amounts of bias. In addition, variance can also be estimated appropriately, although variance is overestimated when cell frequencies are small.

Release date: 2022-06-21
10. Changes in chronic disease risk factors and current exercise habits among Canadian adults living with and without a child during the COVID-19 pandemic
Articles and reports: 82-003-X202200400001
Description:
Canadians have been gravely impacted by the COVID-19 pandemic, and adults living with children may have been disproportionately impacted. The objective of this study was to describe changes in chronic disease risk factors and current exercise habits among adults living with and without a child younger than 18 years old.

Release date: 2022-04-20

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Date modified:: 2024-04-19