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Results
All (180)
All (180) (40 to 50 of 180 results)
- 36-23-0002Description: Input-output (IO) models are generally used to simulate the economic impacts of an expenditure on a given basket of goods and services or the output of one or several industries. The simulation results from a “shock” to an IO model will show the direct, indirect and induced impacts on Gross Domestic Product (GDP), which industries benefit the most, the number of jobs created, estimates of indirect taxes and subsidies generated, etc. The model also includes an estimate of the impact on interprovincial trade flows. IO price, energy, and tax models may also be available depending on the availability of resources. For more details, ask us for the Guide to using the input-output simulation model, available upon request.Release date: 2020-11-23
- 19-22-0004Description: One of the main objectives of statistics is to distill data into information which can be summarized and easily understood. Data visualizations, which include graphs and charts, are powerful ways of doing so. The purpose of this information session is to provide examples of common graphs and charts, highlight practical advice to help the audience choose the right display for their data, and identify what to avoid and why. An overall objective is to build capacity and increase understanding of fundamental techniques which foster accurate and effective dissemination of statistics and research findings. https://www.statcan.gc.ca/en/wtc/information/19220004Release date: 2020-10-30
- Articles and reports: 82-003-X202000700002Description:
This paper's objectives are to examine the feasibility of pooling linked population health surveys from three countries, facilitate the examination of health behaviours, and present useful information to assist in the planning of international population health surveillance and research studies.
Release date: 2020-07-29 - 19-23-0005Description:
The service aims to provide clients with various advice and customise training on statistical methodology.
Release date: 2020-06-12 - Articles and reports: 62F0014M2020008Description: This document describes the methodology and data source for the provincial monthly average retail prices table. This supplement also explains the difference between the Consumer Price Index and average retail prices in context of inflation.Release date: 2020-06-10
- Surveys and statistical programs – Documentation: 75F0002M2020001Description:
This note provides the definition of a first-time homebuyer concept used in the 2018 Canadian Housing Survey (CHS). It also includes the methodology used to identify first-time homebuyers and provides sensitivity analysis under alternative methodologies.
Release date: 2020-01-15 - 47. The value of data in Canada: Experimental estimates ArchivedArticles and reports: 13-605-X201900100009Description:
In this paper a preliminary set of statistical estimates of the amounts invested in Canadian data, databases and data science in recent years are presented. The results indicate rapid growth in investment in data, databases and data science over the last three decades and a significant accumulation of these kinds of capital over time.
Release date: 2019-07-10 - Articles and reports: 13-605-X201900100008Description:
This paper aims to expand the current national accounting concepts and statistical methods for measuring data in order to shed light on some highly consequential changes in society that are related to the rising usage of data. The paper concludes by discussing possible methods that can be used to assign an economic value to the various elements in the information chain and tests these concepts and methods by presenting results for Canada as a first attempt to measure the value of data.
Release date: 2019-06-24 - Surveys and statistical programs – Documentation: 15F0004XDescription:
The input-output (IO) models are generally used to simulate the economic impacts of an expenditure on a given basket of goods and services or the output of one or several industries. The simulation results from a "shock" to an IO model will show the direct, indirect and induced impacts on GDP, which industries benefit the most, the number of jobs created, estimates of indirect taxes and subsidies generated, etc. For more details, ask us for the Guide to using the input-output simulation model, available free of charge upon request.
At various times, clients have requested the use of IO price, energy, tax and market models. Given their availability, arrangements can be made to use these models on request.
The national IO model was not released in 2015 or 2016.
Release date: 2019-04-04 - Surveys and statistical programs – Documentation: 15F0009XDescription:
The input-output (IO) models are generally used to simulate the economic impacts of an expenditure on a given basket of goods and services or the output of one or several industries. The simulation results from a "shock" to an IO model will show the direct, indirect and induced impacts on GDP, which industries benefit the most, the number of jobs created, estimates of indirect taxes and subsidies generated, etc. For more details, ask us for the Guide to using the input-output simulation model, available free of charge upon request.
At various times, clients have requested the use of IO price, energy, tax and market models. Given their availability, arrangements can be made to use these models on request.
The interprovincial IO model was not released in 2015 or 2016.
Release date: 2019-04-04
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Data (1)
Data (1) ((1 result))
- Public use microdata: 12M0022XDescription:
This package was designed to enable users to access and manipulate the microdata file for Cycle 22 (2008) of the General Social Survey (GSS). It contains information on the objectives, methodology and estimation procedures, as well as guidelines for releasing estimates based on the survey. Cycle 22 collected data from persons 15 years and over living in private households in Canada, excluding residents of the Yukon, Northwest Territories and Nunavut; and full-time residents of institutions. The survey covered a range of topics such as social networks, and social and civic participation. Information was also collected on major changes in respondents' lives in the last 12 months, the resources they used during these transitions and unmet needs for help. Questions were also asked on trust, sense of belonging, volunteering and unpaid work.
Release date: 2010-03-05
Analysis (150)
Analysis (150) (0 to 10 of 150 results)
- Articles and reports: 11-633-X2025005Description: This study presents an approach to model changes in the numbers of elementary, secondary and postsecondary students who are immigrants (including both permanent residents and non permanent residents) in response to changes in overall immigration levels.Release date: 2025-12-22
- Articles and reports: 12-001-X202500100007Description: We introduce a novel approach to model-assisted calibration estimation in survey sampling using generalized entropy. The method builds upon recent work by Kwon, Kim and Qiu (2024) and extends it to a model-assisted framework. Unlike traditional calibration techniques, this approach employs a generalized entropy function as the objective for optimization and incorporates a debiasing calibration constraint to ensure design consistency. The proposed estimator is shown to be asymptotically equivalent to an augmented generalized regression (GREG) estimator. It allows for unequal model variance, potentially improving efficiency when the sampling design is informative. The paper presents both design-based and model-based justifications for the method, along with asymptotic properties and variance estimation techniques. Computational aspects are discussed, including an unconstrained optimization approach that facilitates implementation, especially for high-dimensional auxiliary variables. The method’s performance is evaluated through a simulation study, demonstrating its effectiveness in improving estimation efficiency, particularly when the sampling design is informative.Release date: 2025-06-30
- Articles and reports: 12-001-X202500100008Description: Tightened budgets, continuing decrease of response rates in traditional probability surveys and increasing pressure by users for more timely data, has stimulated research on the use of nonprobability sample data, such as administrative records, web scraping, mobile phone data and voluntary internet surveys, for inference on finite population parameters like means and totals. These data are often easier, faster and cheaper to collect than traditional probability samples. However, a major concern with the use of this kind of data for official statistics is their nonrepresentativeness due to possible selection bias, which if not accounted for properly, could bias the inference. In this article, we review and discuss methods considered in the literature to deal with this problem and propose new methods, distinguishing between methods based on integration of the nonprobability sample with an appropriate probability sample, and methods that base the inference solely on the nonprobability sample. Empirical illustrations, based on simulated data are provided.Release date: 2025-06-30
- Articles and reports: 12-001-X202500100009Description: BigData users and the BigData research community are expanding rapidly, while statisticians at large are seemingly becoming divided between those who are enthusiastic and those who are concerned, if not downright hostile. Is BigData also a big step ahead, truly advancing our ability to extract meaningful information and actual knowledge from data? Is BigData underplaying traditional statistical inference as we know it, supplanting survey methodology as a low-cost futuristic option? In this paper I will attempt to unravel the multifaceted relationship bridging BigData to sampling methodology. Starting by reasoning why it should be interesting to look at BigData from a sampling statistician’s perspective, I will delve deeper into the somewhat ambiguous definition of BigData and share some very personal considerations and views on the matter. In the process, several open questions will arise while discussing a personal selection of insights that are traceable through the vast body of statistical literature around BigData and sampling methodology. The discussion will take various angles explored across nine key points, and it will conclude with a forward-looking perspective on a main challenge for future research: addressing the strong assumptions needed to manage deviations from purely randomized data collection.Release date: 2025-06-30
- Articles and reports: 12-001-X202500100011Description: This discussion examines some advancements in survey design and estimation, inspired by the comprehensive appraisal of Professors Jon Rao and Sharon Lohr on current trends in the field. It delves into three specific areas: balanced sampling, calibration, and small area estimation. Probabilistic balanced sampling methods, such as the cube method and penalized balanced sampling, are explored, with an emphasis on addressing emerging challenges, including extensions to linear mixed models, nonparametric regression models, and spatially balanced designs. Calibration is discussed using a modular framework that incorporates modern regression techniques, and highlights innovative uses of model calibration for data editing and causal inference. Small area estimation is considered in the context of latent variable modeling and data integration, emphasizing its role when the variable(s) of interest cannot be measured either directly or without error. Applications in integrating probability and non-probability data and conducting causal analysis at local level are also discussed.Release date: 2025-06-30
- Articles and reports: 12-001-X202500100012Description: In this discussion, we complement the excellent overview by Profs. Lohr and Rao with some additional topics. The first topic is a call for more recognition of the central role of modeling in survey estimation. The second is a brief discussion of the use of partial frame information in survey design. Finally, we draw the attention to recent increases of synthetic methods, in particular, multilevel regression and poststratification (MRP) in small area estimation applications.Release date: 2025-06-30
- 7. Comments by Mary E. Thompson on “Progress in survey science and practice: Yesterday-today-tomorrow”Articles and reports: 12-001-X202500100016Description: These comments on C.-E. Särndal’s paper, “Progress in survey science and practice: yesterday-today-tomorrow”, will touch on probability sampling fundamentals, progress through competing approaches to inference, connections with other parts of statistics, and data in the twenty-first century.Release date: 2025-06-30
- Journals and periodicals: 11-632-XDescription: The newsletter offers information aimed at three main groups, businesses (small to medium), communities and ethno-cultural groups/communities. Articles and outreach materials will assist their understanding of national and local data from the many relevant sources found on the Statistics Canada website.Release date: 2025-01-16
- Stats in brief: 89-20-00062024003Description: This video is intended for professionals, policymakers, and researchers who are interested in understanding how data linkage can be used to gain deeper insights into various issues. It demonstrates how combining data from different sources can help address gaps in information, leading to better-informed policies and improved outcomes.Release date: 2024-11-25
- Articles and reports: 11-522-X202200100017Description: In this paper, we look for presence of heterogeneity in conducting impact evaluations of the Skills Development intervention delivered under the Labour Market Development Agreements. We use linked longitudinal administrative data covering a sample of Skills Development participants from 2010 to 2017. We apply a causal machine-learning estimator as in Lechner (2019) to estimate the individualized program impacts at the finest aggregation level. These granular impacts reveal the distribution of net impacts facilitating further investigation as to what works for whom. The findings suggest statistically significant improvements in labour market outcomes for participants overall and for subgroups of policy interest.Release date: 2024-06-28
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Reference (25)
Reference (25) (0 to 10 of 25 results)
- Surveys and statistical programs – Documentation: 11-633-X2024004Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 40 years.Release date: 2024-12-09
- Notices and consultations: 95-635-XDescription: To stay relevant, preparing for a new Census of Agriculture requires a thorough evaluation of data requirements. Before each census, Statistics Canada conducts consultations to solicit input and feedback on the Census of Agriculture's content. This report describes those consultations and the process that was followed to test and determine which topics could be potentially retained for the next census.Release date: 2024-11-27
- Surveys and statistical programs – Documentation: 11-633-X2024001Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 35 years.Release date: 2024-01-22
- Surveys and statistical programs – Documentation: 84-538-XGeography: CanadaDescription: This electronic publication presents the methodology underlying the production of the life tables for Canada, provinces and territories.Release date: 2023-08-28
- Surveys and statistical programs – Documentation: 11-633-X2022009Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 35 years.
This report will discuss the IMDB data sources, concepts and variables, record linkage, data processing, dissemination, data evaluation and quality indicators, comparability with other immigration datasets, and the analyses possible with the IMDB.
Release date: 2022-12-05 - Surveys and statistical programs – Documentation: 98-304-XDescription: The Guide to the Census of Population is a reference document that describes the various phases of the 2021 Census of Population. The guide provides an overview of content determination, sampling design, collection, data processing, data quality assessment, confidentiality guidelines and dissemination. It also includes response rates and other data quality information. This product may be useful to both new and experienced users who wish to familiarize themselves with and find specific information about the 2021 Census of Population.
The Guide to the Census of Population combines information previously available in the Overview of the Census, National Household Survey User Guide and the Data Quality and Confidentiality Standards and Guidelines from 2011.
Release date: 2022-11-30 - Surveys and statistical programs – Documentation: 11-633-X2021008Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 35 years. The IMDB includes Immigration, Refugees and Citizenship Canada (IRCC) administrative records which contain exhaustive information about immigrants who were admitted to Canada since 1952. It also includes data about non-permanent residents who have been issued temporary resident permits since 1980. This report will discuss the IMDB data sources, concepts and variables, record linkage, data processing, dissemination, data evaluation and quality indicators, comparability with other immigration datasets, and the analyses possible with the IMDB.Release date: 2021-12-06
- Surveys and statistical programs – Documentation: 11-633-X2021002Description:
The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 35 years. The IMDB includes Immigration, Refugees and Citizenship Canada (IRCC) administrative records which contain exhaustive information about immigrants who were admitted to Canada since 1952. It also includes data about non-permanent residents who have been issued temporary resident permits since 1980. This report will discuss the IMDB data sources, concepts and variables, record linkage, data processing, dissemination, data evaluation and quality indicators, comparability with other immigration datasets, and the analyses possible with the IMDB.
Release date: 2021-02-01 - Surveys and statistical programs – Documentation: 75F0002M2020001Description:
This note provides the definition of a first-time homebuyer concept used in the 2018 Canadian Housing Survey (CHS). It also includes the methodology used to identify first-time homebuyers and provides sensitivity analysis under alternative methodologies.
Release date: 2020-01-15 - Surveys and statistical programs – Documentation: 15F0004XDescription:
The input-output (IO) models are generally used to simulate the economic impacts of an expenditure on a given basket of goods and services or the output of one or several industries. The simulation results from a "shock" to an IO model will show the direct, indirect and induced impacts on GDP, which industries benefit the most, the number of jobs created, estimates of indirect taxes and subsidies generated, etc. For more details, ask us for the Guide to using the input-output simulation model, available free of charge upon request.
At various times, clients have requested the use of IO price, energy, tax and market models. Given their availability, arrangements can be made to use these models on request.
The national IO model was not released in 2015 or 2016.
Release date: 2019-04-04