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All (17)
All (17) (0 to 10 of 17 results)
- Data Visualization: 71-607-X2022012Description:
This interactive dashboard provides an overview of population projections on immigration and diversity prepared using the Demosim microsimulation projection model. Showing results coming from several projection scenarios, this tool allows users to quickly and easily explore data-such as population counts by geography, age group and generation status. Information is presented for the overall Canadian population as well as for each racialized group at various geographic levels including census metropolitan areas, provinces and territories.
Release date: 2022-10-06 - Articles and reports: 17-20-00012022001Description:
This document briefly describes the assumptions and scenarios that were selected for the population projections for Canada and its regions on the themes of immigration and diversity for the period 2016 to 2041, produced using the Demosim microsimulation projection model.
Release date: 2022-09-08 - Articles and reports: 17-20-0001Description: Demosim: Reports and Analytical Studies, published occasionally by the Centre for Demography of Statistics Canada, features analytical, technical and methodological documents related to Demosim, a microsimulation model designed to produce demographic projections for specific populations such as Indigenous peoples, immigrants and racialized groups. These documents are intended for a broad audience including demographers, researchers, policy makers as well as members of the general public interested in Canadian population trends.Release date: 2022-09-08
- Stats in brief: 11-627-M2021066Description:
This infographic briefly describes key results from the projections of the Indigenous populations in Canada for the period 2016 to 2041. Using different projection scenarios, it presents projection results through various demographic indicators. These projections are produced using the Demosim microsimulation projection model.
Release date: 2021-10-06 - Stats in brief: 11-627-M2021067Description:
This infographic briefly describes key results from the demographic projections of the First Nations people in Canada for the period 2016 to 2041. Using different projection scenarios, it presents projection results through various demographic indicators. These projections are produced using the Demosim microsimulation projection model.
Release date: 2021-10-06 - Stats in brief: 11-627-M2021068Description:
This infographic briefly describes key results from the demographic projections of the Métis in Canada for the period 2016 to 2041. Using different projection scenarios, it presents projection results through various demographic indicators. These projections are produced using the Demosim microsimulation projection model.
Release date: 2021-10-06 - Stats in brief: 11-627-M2021069Description:
This infographic briefly describes key results from the demographic projections of the Inuit in Canada for the period 2016 to 2041. Using different projection scenarios, it presents projection results through various demographic indicators. These projections are produced using the Demosim microsimulation projection model.
Release date: 2021-10-06 - Articles and reports: 17-20-00012021001Description:
This document briefly describes the methods and data sources used in the preparation of the projections of the Indigenous populations and households in Canada for the period 2016 to 2041, produced using the Demosim microsimulation projection model. It also includes a description of the assumptions and scenarios that were selected for this projection exercise.
Release date: 2021-10-06 - Articles and reports: 85-002-X201900100014Description:
This Juristat article explores current conditions in Saskatchewan and the province's criminal justice system. Projections are presented to demonstrate how positive outcomes can be reached through possible education-related intervention. Educational attainment was selected for analysis as research has often explored the link between education and criminal behaviour. Projections were created using Statistics Canada's Demosim microsimulation model.
Release date: 2019-09-19 - 10. The DYSEM Microsimulation Modelling Platform ArchivedArticles and reports: 11-633-X2017008Description:
The DYSEM microsimulation modelling platform provides a demographic and socioeconomic core that can be readily built upon to develop custom dynamic microsimulation models or applications. This paper describes DYSEM and provides an overview of its intended uses, as well as the methods and data used in its development.
Release date: 2017-07-28
Data (1)
Data (1) ((1 result))
- Data Visualization: 71-607-X2022012Description:
This interactive dashboard provides an overview of population projections on immigration and diversity prepared using the Demosim microsimulation projection model. Showing results coming from several projection scenarios, this tool allows users to quickly and easily explore data-such as population counts by geography, age group and generation status. Information is presented for the overall Canadian population as well as for each racialized group at various geographic levels including census metropolitan areas, provinces and territories.
Release date: 2022-10-06
Analysis (14)
Analysis (14) (0 to 10 of 14 results)
- Articles and reports: 17-20-00012022001Description:
This document briefly describes the assumptions and scenarios that were selected for the population projections for Canada and its regions on the themes of immigration and diversity for the period 2016 to 2041, produced using the Demosim microsimulation projection model.
Release date: 2022-09-08 - Articles and reports: 17-20-0001Description: Demosim: Reports and Analytical Studies, published occasionally by the Centre for Demography of Statistics Canada, features analytical, technical and methodological documents related to Demosim, a microsimulation model designed to produce demographic projections for specific populations such as Indigenous peoples, immigrants and racialized groups. These documents are intended for a broad audience including demographers, researchers, policy makers as well as members of the general public interested in Canadian population trends.Release date: 2022-09-08
- Stats in brief: 11-627-M2021066Description:
This infographic briefly describes key results from the projections of the Indigenous populations in Canada for the period 2016 to 2041. Using different projection scenarios, it presents projection results through various demographic indicators. These projections are produced using the Demosim microsimulation projection model.
Release date: 2021-10-06 - Stats in brief: 11-627-M2021067Description:
This infographic briefly describes key results from the demographic projections of the First Nations people in Canada for the period 2016 to 2041. Using different projection scenarios, it presents projection results through various demographic indicators. These projections are produced using the Demosim microsimulation projection model.
Release date: 2021-10-06 - Stats in brief: 11-627-M2021068Description:
This infographic briefly describes key results from the demographic projections of the Métis in Canada for the period 2016 to 2041. Using different projection scenarios, it presents projection results through various demographic indicators. These projections are produced using the Demosim microsimulation projection model.
Release date: 2021-10-06 - Stats in brief: 11-627-M2021069Description:
This infographic briefly describes key results from the demographic projections of the Inuit in Canada for the period 2016 to 2041. Using different projection scenarios, it presents projection results through various demographic indicators. These projections are produced using the Demosim microsimulation projection model.
Release date: 2021-10-06 - Articles and reports: 17-20-00012021001Description:
This document briefly describes the methods and data sources used in the preparation of the projections of the Indigenous populations and households in Canada for the period 2016 to 2041, produced using the Demosim microsimulation projection model. It also includes a description of the assumptions and scenarios that were selected for this projection exercise.
Release date: 2021-10-06 - Articles and reports: 85-002-X201900100014Description:
This Juristat article explores current conditions in Saskatchewan and the province's criminal justice system. Projections are presented to demonstrate how positive outcomes can be reached through possible education-related intervention. Educational attainment was selected for analysis as research has often explored the link between education and criminal behaviour. Projections were created using Statistics Canada's Demosim microsimulation model.
Release date: 2019-09-19 - 9. The DYSEM Microsimulation Modelling Platform ArchivedArticles and reports: 11-633-X2017008Description:
The DYSEM microsimulation modelling platform provides a demographic and socioeconomic core that can be readily built upon to develop custom dynamic microsimulation models or applications. This paper describes DYSEM and provides an overview of its intended uses, as well as the methods and data used in its development.
Release date: 2017-07-28 - Articles and reports: 12-001-X201600114542Description:
The restricted maximum likelihood (REML) method is generally used to estimate the variance of the random area effect under the Fay-Herriot model (Fay and Herriot 1979) to obtain the empirical best linear unbiased (EBLUP) estimator of a small area mean. When the REML estimate is zero, the weight of the direct sample estimator is zero and the EBLUP becomes a synthetic estimator. This is not often desirable. As a solution to this problem, Li and Lahiri (2011) and Yoshimori and Lahiri (2014) developed adjusted maximum likelihood (ADM) consistent variance estimators which always yield positive variance estimates. Some of the ADM estimators always yield positive estimates but they have a large bias and this affects the estimation of the mean squared error (MSE) of the EBLUP. We propose to use a MIX variance estimator, defined as a combination of the REML and ADM methods. We show that it is unbiased up to the second order and it always yields a positive variance estimate. Furthermore, we propose an MSE estimator under the MIX method and show via a model-based simulation that in many situations, it performs better than other ‘Taylor linearization’ MSE estimators proposed recently.
Release date: 2016-06-22
Reference (2)
Reference (2) ((2 results))
- Surveys and statistical programs – Documentation: 11-522-X19990015648Description:
We estimate the parameters of a stochastic model for labour force careers involving distributions of correlated durations employed, unemployed (with and without job search) and not in the labour force. If the model is to account for sub-annual labour force patterns as well as advancement towards retirement, then no single data source is adequate to inform it. However, it is possible to build up an approximation from a number of different sources.
Release date: 2000-03-02 - Surveys and statistical programs – Documentation: 11-522-X19980015034Description:
A model of secondary school progression has been estimated using data from the 1991 School Leavers Survey conducted by Statistics Canada. The data on which the school progression model was based comprised current educational status and responses to retrospective questions on the timing of schooling events. These data were sufficient for approximate reconstruction of educational event histories of each respondent. The school progression model was designed to be included in a larger, continuous time micro-simulation model. Its main features involve estimation -- by age, month of birth and season for both sexes in each province -- of rates of graduation, of dropout, of return and of dropout graduation. Estimation was reinforced with auxiliary 1991 Census and administative data.
Release date: 1999-10-22
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