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All (160)

All (160) (0 to 10 of 160 results)

1. 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
2. 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
3. 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
4. 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
5. 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
6. Unravelling the story about household textile and e-waste disposal in Canada
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
7. Extensions of indicators on base erosion and profit shifting in Canada
Articles and reports: 11-621-M2021005
Description:
Multinational enterprises (MNEs) have been drivers of globalization. These enterprises have taken advantage of innovations in logistics and communications technology over the past four decades to diversify their supply chains and expand into new markets. Operating internationally, however, also allows MNEs to take advantage of tax systems which were designed for a less integrated era. For example, MNEs can arrange for profits to be 'shifted' by charging affiliates in high tax locations prices above market rates in transactions with affiliates in lower tax regions. These behaviours are referred to as base erosion and profit shifting (BEPS), and, although not illegal, they impact government revenues worldwide.
Release date: 2021-12-02
8. Applying the data science approach to COVID-19 epidemiological modelling to inform PPE demand and supply in Canada Archived
Articles and reports: 11-522-X202100100017
Description:
The outbreak of the COVID-19 pandemic required the Government of Canada to provide relevant and timely information to support decision-making around a host of issues, including personal protective equipment (PPE) procurement and deployment. Our team built a compartmental epidemiological model from an existing code base to project PPE demand under a range of epidemiological scenarios. This model was further enhanced using data science techniques, which allowed for the rapid development and dissemination of model results to inform policy decisions.

Key Words: COVID-19; SARS-CoV-2; Epidemiological model; Data science; Personal Protective Equipment (PPE); SEIR

Release date: 2021-10-22
9. Predicting transitions into and out of poverty using machine learning Archived
Articles and reports: 11-522-X202100100003
Description:
The increasing size and richness of digital data allow for modeling more complex relationships and interactions, which is the strongpoint of machine learning. Here we applied gradient boosting to the Dutch system of social statistical datasets to estimate transition probabilities into and out of poverty. Individual estimates are reasonable, but the main advantages of the approach in combination with SHAP and global surrogate models are the simultaneous ranking of hundreds of features by their importance, detailed insight into their relationship with the transition probabilities, and the data-driven identification of subpopulations with relatively high and low transition probabilities. In addition, we decompose the difference in feature importance between general and subpopulation into a frequency and a feature effect. We caution for misinterpretation and discuss future directions.
Key Words: Classification; Explainability; Gradient boosting; Life event; Risk factors; SHAP decomposition.

Release date: 2021-10-15
10. Bridging the gap between the displaced and in-demand occupations Archived
Articles and reports: 11-522-X202100100004
Description:
With labour market uncertainty increasing across Canada, there is a need for innovative ways to help displaced workers to re-skill/up-skill and potentially pivot to in-demand occupations. In our study, we present a unique approach to bridge the gap between the displaced and in-demand occupations and provide a machine learning framework that may be able to forecast employment by NAICS for 6 months. We have combined the monthly employment data from Statistics Canada’s Survey of Employment and Payroll Hours, and the monthly job ads counts from Burning Glass to achieve our goal. Our approach consists of three steps: 1. Finding the displaced occupations in Alberta over the last 7 years based on the integrated actual employment and job ads count data. Step. 2. Using the list of displaced occupations, a unique pivot graph is developed to map a displaced occupation to a list of in-demand occupations which have skills similar to the chosen displaced occupation. Step 3. Applying SARIMA and SARIMAX models to forecast employment for 6 months. The above approaches are aimed at assisting public policy and planning
Key Words: Employment; Labour Market; Job Ads; Skills; Time Series Analysis; Forecasting.

Release date: 2021-10-15

Stats in brief (7)

Stats in brief (7) ((7 results))

1. Unravelling the story about household textile and e-waste disposal in Canada
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
2. Stats are on the menu! Canada’s restaurant industry
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
3. 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
4. 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
5. 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
6. 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
7. 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 (153)

Articles and reports (153) (0 to 10 of 153 results)

1. 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
2. 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
3. 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
4. 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
5. 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
6. Extensions of indicators on base erosion and profit shifting in Canada
Articles and reports: 11-621-M2021005
Description:
Multinational enterprises (MNEs) have been drivers of globalization. These enterprises have taken advantage of innovations in logistics and communications technology over the past four decades to diversify their supply chains and expand into new markets. Operating internationally, however, also allows MNEs to take advantage of tax systems which were designed for a less integrated era. For example, MNEs can arrange for profits to be 'shifted' by charging affiliates in high tax locations prices above market rates in transactions with affiliates in lower tax regions. These behaviours are referred to as base erosion and profit shifting (BEPS), and, although not illegal, they impact government revenues worldwide.
Release date: 2021-12-02
7. Applying the data science approach to COVID-19 epidemiological modelling to inform PPE demand and supply in Canada Archived
Articles and reports: 11-522-X202100100017
Description:
The outbreak of the COVID-19 pandemic required the Government of Canada to provide relevant and timely information to support decision-making around a host of issues, including personal protective equipment (PPE) procurement and deployment. Our team built a compartmental epidemiological model from an existing code base to project PPE demand under a range of epidemiological scenarios. This model was further enhanced using data science techniques, which allowed for the rapid development and dissemination of model results to inform policy decisions.

Key Words: COVID-19; SARS-CoV-2; Epidemiological model; Data science; Personal Protective Equipment (PPE); SEIR

Release date: 2021-10-22
8. Predicting transitions into and out of poverty using machine learning Archived
Articles and reports: 11-522-X202100100003
Description:
The increasing size and richness of digital data allow for modeling more complex relationships and interactions, which is the strongpoint of machine learning. Here we applied gradient boosting to the Dutch system of social statistical datasets to estimate transition probabilities into and out of poverty. Individual estimates are reasonable, but the main advantages of the approach in combination with SHAP and global surrogate models are the simultaneous ranking of hundreds of features by their importance, detailed insight into their relationship with the transition probabilities, and the data-driven identification of subpopulations with relatively high and low transition probabilities. In addition, we decompose the difference in feature importance between general and subpopulation into a frequency and a feature effect. We caution for misinterpretation and discuss future directions.
Key Words: Classification; Explainability; Gradient boosting; Life event; Risk factors; SHAP decomposition.

Release date: 2021-10-15
9. Bridging the gap between the displaced and in-demand occupations Archived
Articles and reports: 11-522-X202100100004
Description:
With labour market uncertainty increasing across Canada, there is a need for innovative ways to help displaced workers to re-skill/up-skill and potentially pivot to in-demand occupations. In our study, we present a unique approach to bridge the gap between the displaced and in-demand occupations and provide a machine learning framework that may be able to forecast employment by NAICS for 6 months. We have combined the monthly employment data from Statistics Canada’s Survey of Employment and Payroll Hours, and the monthly job ads counts from Burning Glass to achieve our goal. Our approach consists of three steps: 1. Finding the displaced occupations in Alberta over the last 7 years based on the integrated actual employment and job ads count data. Step. 2. Using the list of displaced occupations, a unique pivot graph is developed to map a displaced occupation to a list of in-demand occupations which have skills similar to the chosen displaced occupation. Step 3. Applying SARIMA and SARIMAX models to forecast employment for 6 months. The above approaches are aimed at assisting public policy and planning
Key Words: Employment; Labour Market; Job Ads; Skills; Time Series Analysis; Forecasting.

Release date: 2021-10-15
10. Statistics Canada’s Seasonal Adjustment Dashboard Archived
Articles and reports: 11-522-X202100100020
Description:
Seasonal adjustment of time series at Statistics Canada is performed using the X-12-ARIMA method. For most statistical programs performing seasonal adjustment, subject matter experts (SMEs) are responsible for managing the program and for verification, analysis and dissemination of the data, while methodologists from the Time Series Research and Analysis Center (TSRAC) are responsible for developing and maintaining the seasonal adjustment process and for providing support on seasonal adjustment to SMEs. A visual summary report called the seasonal adjustment dashboard has been developed in R Shiny by the TSRAC to build capacity to interpret seasonally adjusted data and to reduce the resources needed to support seasonal adjustment. It is currently being made available internally to assist SMEs to interpret and explain seasonally adjusted results. The summary report includes graphs of the series across time, as well as summaries of individual seasonal and calendar effects and patterns. Additionally, key seasonal adjustment diagnostics are presented and the net effect of seasonal adjustment is decomposed into its various components. This paper gives a visual representation of the seasonal adjustment process, while demonstrating the dashboard and its interactive functionality.
Key Words: Time Series; X-12-ARIMA; Summary Report; R Shiny.
Release date: 2021-10-15

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Date modified:: 2023-01-30