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All (24,457) (24,400 to 24,410 of 24,457 results)

24,401. Natural Resources Indicators (NRI)
Surveys and statistical programs – Documentation: 5367
Description: The Natural Resource Indicators (NRI) provide timely information which facilitates ongoing monitoring and analysis of the economic contribution of the natural resources sector in Canada. This sector is split between four subsectors; energy, minerals and mining, forestry, and hunting, fishing and water. A downstream natural resources sector is also measured.
24,402. Distributions of household economic accounts for wealth of Canadian households
Surveys and statistical programs – Documentation: 5369
Description: The Distributions of Household Economic Accounts (DHEA) for wealth provide information on the economic well-being and financial stability of households in Canada. The DHEA help address questions such as vulnerabilities and inequality across different groups of households and are an important complement to standard quarterly and annual indicators related to the economy.
24,403. Distributions of household economic accounts for income, consumption and saving of Canadian households
Surveys and statistical programs – Documentation: 5370
Description: The Distributions of Household Economic Accounts (DHEA) for income, consumption and saving provide information on the economic well-being and financial stability of households in Canada. The DHEA help address questions such as vulnerabilities and inequality across different groups of households and are an important complement to standard quarterly and annual indicators related to the economy.
24,404. Canadian Survey on Early Learning and Child Care (CSELCC)
Surveys and statistical programs – Documentation: 5371
Description: The survey asks parents and guardians about the arrangements they use for their child aged 0 to 5, including the associated costs, the difficulties they may have faced when looking for care, and what their preferences for child care are. This survey also collects information on parents' and guardian's labour market participation to better understand the interaction between work and the use of early learning and child care arrangements. Results from this survey will be used to help improve the Canada-wide early learning and child care system and provide Canadians with a strong baseline of data to measure progress and changes to the system.
24,405. Covid 19 Restrictions indexes; Daily
Surveys and statistical programs – Documentation: 5373
Description: This program produces indexes for the stringency of Covid-19 restrictions across the provinces and territories.
24,406. Covid 19 Restrictions indexes; Monthly
Surveys and statistical programs – Documentation: 5374
Description: This program produces indexes for the stringency of Covid-19 restrictions across the provinces and territories.
24,407. Labour Market Indicators
Surveys and statistical programs – Documentation: 5375
Description: The purpose of this survey is to identify emerging trends in the Canadian labour market.
24,408. Canadian System of Environmental-Economic Accounts - Environmental Tax Account
Surveys and statistical programs – Documentation: 5376
Description: The Environmental Tax Account (ETA) is one of the elements of the United Nations System of Environmental-Economic Accounting - Central Framework (SEEA-CF), which was adopted as an international standard in 2012. This account records, in monetary units, government revenues generated from environmental tax from industry, government, non-profits and households.
24,409. Labour Market and Socio-economic Indicators
Surveys and statistical programs – Documentation: 5377
Description: The purpose of this survey is to identify changing dynamics within the Canadian labour market and measure important socio-economic indicators.
24,410. Survey Series on People and their Communities
Surveys and statistical programs – Documentation: 5378
Description: The Survey Series on People and their Communities (SSPC) involves creating a panel of people who agree to complete a series of short surveys. This is the third time that Statistics Canada is conducting this type of survey.

Data (12,062)

Data (12,062) (0 to 10 of 12,062 results)

1. Selected indicators of quality of life in Canada
Data Visualization: 71-607-X2022007
Description: This dashboard provides an interactive view of eight indicators from the Quality of Life Framework for Canada: Life satisfaction, sense of meaning and purpose, future outlook, loneliness, someone to count on, sense of belonging to local community, perceived mental health, and perceived health. The data can be organized by province, gender and other characteristics such as age group. This dashboard is based on quarterly data from the Canadian Social Survey.
Release date: 2024-08-15
2. Extractive Sector Transparency Measures Act Data Portal
Data Visualization: 71-607-X2022008
Description: The Extractive Sector Transparency Measures Act (ESTMA) Data Portal is a collaboration between Statistics Canada and Natural Resources Canada, which administers the ESTMA. The ESTMA helps the Government of Canada deter corruption in the extractive sector by requiring extractive entities that are active in Canada to publicly disclose, on an annual basis, certain types of payments made to governments in Canada and abroad. The goal of the data portal is to increase the accessibility and utility of the payment information collected under the ESTMA by bringing together all available ESTMA data in one online location, and further enriching the payment data with analytical functions that help users to leverage the complete ESTMA dataset. The database has also been designed with mobility in mind to ensure that users and stakeholders have mobile access to ESTMA data.
Release date: 2024-08-15
3. Traffic Flow Dashboard
Data Visualization: 71-607-X2022018
Description: This dashboard shows traffic count data that is obtained from traffic camera imagery using a computer vision-based system developed at the Data Exploration and Integration Lab (DEIL) at Statistics Canada. The system periodically pulls traffic imagery from the Application Programmable Interfaces (APIs) of municipal and provincial traffic camera programs. Vehicle detection was implemented using the open source You Only Look Once version 3 (YOLOv3) object detection model that was trained on the Common Objects in Context (COCO) dataset. The output of the model is used to generates real-time counts of the detected vehicles (cars, trucks, buses, motorcycles).
Release date: 2024-08-15
4. Canadian Economic Tracker
Data Visualization: 71-607-X2023022
Description: The Canadian Economic Tracker presents selected monthly indicators from Statistics Canada's Common Output Database Repository (CODR) to highlight interrelated dynamics within the Canadian economy.
Release date: 2024-08-15
5. Statistics Canada - Data Visualization Products
Data Visualization: 71-607-X
Description: Statistics Canada produces a variety of interactive visualization tools that present data in a graphical form. These tools provide a useful way of interpreting trends behind our data on various social and economic topics.
Release date: 2024-08-15
6. Bank of Canada, money market and other interest rates
Table: 10-10-0139-01
Geography: Canada
Frequency: Daily
Description: This table contains 39 series, with data for starting from 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Financial market statistics (39 items: Government of Canada Treasury Bills, 1-month (composite rates); Government of Canada Treasury Bills, 2-month (composite rates); Government of Canada Treasury Bills, 3-month (composite rates);Government of Canada Treasury Bills, 6-month (composite rates); ...).
Release date: 2024-08-15
7. Financial market statistics, as at Tuesday, Bank of Canada
Table: 10-10-0144-01
Geography: Canada
Frequency: Weekly
Description: This table contains 8 series, with data starting from 1992 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada), Rates (8 items: Bank rate; Treasury bill auction - average yields: 3 month; Treasury bill auction - average yields: 6 month; Treasury bill auction - average yields: 1 year; ...).
Release date: 2024-08-15
8. Life satisfaction by gender and province
Table: 13-10-0843-01
Geography: Canada, Geographical region of Canada, Province or territory
Frequency: Occasional
Description: Percentage of persons aged 15 years and over by level of life satisfaction, by gender, for Canada, regions and provinces.
Release date: 2024-08-15
9. Life satisfaction by gender and other selected sociodemographic characteristics
Table: 13-10-0844-01
Geography: Canada
Frequency: Occasional
Description: Percentage of persons aged 15 years and over by level of life satisfaction, by gender and other selected sociodemographic characteristics: age group; immigrant status; visible minority group; Indigenous identity; persons with a disability, difficulty or long-term condition; LGBTQ2+ people; highest certificate, diploma or degree; main activity; and urban and rural areas.
Release date: 2024-08-15
10. Sense of meaning and purpose by gender and province
Table: 13-10-0845-01
Geography: Canada, Geographical region of Canada, Province or territory
Frequency: Occasional
Description: Percentage of persons aged 15 years and over by level of sense of meaning and purpose, by gender, for Canada, regions and provinces.
Release date: 2024-08-15

Analysis (10,025)

Analysis (10,025) (90 to 100 of 10,025 results)

91. National tourism indicators first quarter 2024
Stats in brief: 11-001-X20241783389
Description: Release published in The Daily – Statistics Canada’s official release bulletin
Release date: 2024-06-26
92. Authors’ response to comments on “Handling non-probability samples through inverse probability weighting with an application to Statistics Canada’s crowdsourcing data”: Some new developments on likelihood approaches to estimation of participation probabilities for non-probability samples
Articles and reports: 12-001-X202400100001
Description: Inspired by the two excellent discussions of our paper, we offer some new insights and developments into the problem of estimating participation probabilities for non-probability samples. First, we propose an improvement of the method of Chen, Li and Wu (2020), based on best linear unbiased estimation theory, that more efficiently leverages the available probability and non-probability sample data. We also develop a sample likelihood approach, similar in spirit to the method of Elliott (2009), that properly accounts for the overlap between both samples when it can be identified in at least one of the samples. We use best linear unbiased prediction theory to handle the scenario where the overlap is unknown. Interestingly, our two proposed approaches coincide in the case of unknown overlap. Then, we show that many existing methods can be obtained as a special case of a general unbiased estimating function. Finally, we conclude with some comments on nonparametric estimation of participation probabilities.
Release date: 2024-06-25
93. Comments by Changbao Wu on “Handling non-probability samples through inverse probability weighting with an application to Statistics Canada’s crowdsourcing data”
Articles and reports: 12-001-X202400100002
Description: We provide comparisons among three parametric methods for the estimation of participation probabilities and some brief comments on homogeneous groups and post-stratification.
Release date: 2024-06-25
94. Comments by Julie Gershunskaya and Vladislav Beresovsky on “Handling non-probability samples through inverse probability weighting with an application to Statistics Canada’s crowdsourcing data”
Articles and reports: 12-001-X202400100003
Description: Beaumont, Bosa, Brennan, Charlebois and Chu (2024) propose innovative model selection approaches for estimation of participation probabilities for non-probability sample units. We focus our discussion on the choice of a likelihood and parameterization of the model, which are key for the effectiveness of the techniques developed in the paper. We consider alternative likelihood and pseudo-likelihood based methods for estimation of participation probabilities and present simulations implementing and comparing the AIC based variable selection. We demonstrate that, under important practical scenarios, the approach based on a likelihood formulated over the observed pooled non-probability and probability samples performed better than the pseudo-likelihood based alternatives. The contrast in sensitivity of the AIC criteria is especially large for small probability sample sizes and low overlap in covariates domains.
Release date: 2024-06-25
95. Handling non-probability samples through inverse probability weighting with an application to Statistics Canada’s crowdsourcing data
Articles and reports: 12-001-X202400100004
Description: Non-probability samples are being increasingly explored in National Statistical Offices as an alternative to probability samples. However, it is well known that the use of a non-probability sample alone may produce estimates with significant bias due to the unknown nature of the underlying selection mechanism. Bias reduction can be achieved by integrating data from the non-probability sample with data from a probability sample provided that both samples contain auxiliary variables in common. We focus on inverse probability weighting methods, which involve modelling the probability of participation in the non-probability sample. First, we consider the logistic model along with pseudo maximum likelihood estimation. We propose a variable selection procedure based on a modified Akaike Information Criterion (AIC) that properly accounts for the data structure and the probability sampling design. We also propose a simple rank-based method of forming homogeneous post-strata. Then, we extend the Classification and Regression Trees (CART) algorithm to this data integration scenario, while again properly accounting for the probability sampling design. A bootstrap variance estimator is proposed that reflects two sources of variability: the probability sampling design and the participation model. Our methods are illustrated using Statistics Canada’s crowdsourcing and survey data.
Release date: 2024-06-25
96. Author’s response to comments on “Exchangeability assumption in propensity-score based adjustment methods for population mean estimation using non-probability samples”
Articles and reports: 12-001-X202400100005
Description: In this rejoinder, I address the comments from the discussants, Dr. Takumi Saegusa, Dr. Jae-Kwang Kim and Ms. Yonghyun Kwon. Dr. Saegusa’s comments about the differences between the conditional exchangeability (CE) assumption for causal inferences versus the CE assumption for finite population inferences using nonprobability samples, and the distinction between design-based versus model-based approaches for finite population inference using nonprobability samples, are elaborated and clarified in the context of my paper. Subsequently, I respond to Dr. Kim and Ms. Kwon’s comprehensive framework for categorizing existing approaches for estimating propensity scores (PS) into conditional and unconditional approaches. I expand their simulation studies to vary the sampling weights, allow for misspecified PS models, and include an additional estimator, i.e., scaled adjusted logistic propensity estimator (Wang, Valliant and Li (2021), denoted by sWBS). In my simulations, it is observed that the sWBS estimator consistently outperforms or is comparable to the other estimators under the misspecified PS model. The sWBS, as well as WBS or ABS described in my paper, do not assume that the overlapped units in both the nonprobability and probability reference samples are negligible, nor do they require the identification of overlap units as needed by the estimators proposed by Dr. Kim and Ms. Kwon.
Release date: 2024-06-25
97. Comments by Takumi Saegusa on “Exchangeability assumption in propensity-score based adjustment methods for population mean estimation using non-probability samples”: Causal inference, non-probability sample, and finite population
Articles and reports: 12-001-X202400100006
Description: In some of non-probability sample literature, the conditional exchangeability assumption is considered to be necessary for valid statistical inference. This assumption is rooted in causal inference though its potential outcome framework differs greatly from that of non-probability samples. We describe similarities and differences of two frameworks and discuss issues to consider when adopting the conditional exchangeability assumption in non-probability sample setups. We also discuss the role of finite population inference in different approaches of propensity scores and outcome regression modeling to non-probability samples.
Release date: 2024-06-25
98. Comments by Jae Kwang Kim and Yonghyun Kwon on “Exchangeability assumption in propensity-score based adjustment methods for population mean estimation using non-probability samples”
Articles and reports: 12-001-X202400100007
Description: Pseudo weight construction for data integration can be understood in the two-phase sampling framework. Using the two-phase sampling framework, we discuss two approaches to the estimation of propensity scores and develop a new way to construct the propensity score function for data integration using the conditional maximum likelihood method. Results from a limited simulation study are also presented.
Release date: 2024-06-25
99. Exchangeability assumption in propensity-score based adjustment methods for population mean estimation using non-probability samples
Articles and reports: 12-001-X202400100008
Description: Nonprobability samples emerge rapidly to address time-sensitive priority topics in different areas. These data are timely but subject to selection bias. To reduce selection bias, there has been wide literature in survey research investigating the use of propensity-score (PS) adjustment methods to improve the population representativeness of nonprobability samples, using probability-based survey samples as external references. Conditional exchangeability (CE) assumption is one of the key assumptions required by PS-based adjustment methods. In this paper, I first explore the validity of the CE assumption conditional on various balancing score estimates that are used in existing PS-based adjustment methods. An adaptive balancing score is proposed for unbiased estimation of population means. The population mean estimators under the three CE assumptions are evaluated via Monte Carlo simulation studies and illustrated using the NIH SARS-CoV-2 seroprevalence study to estimate the proportion of U.S. adults with COVID-19 antibodies from April 01-August 04, 2020.
Release date: 2024-06-25
100. Authors’ response to comments on “Exploring the assumption that commercial online nonprobability survey respondents are answering in good faith”
Articles and reports: 12-001-X202400100009
Description: Our comments respond to discussion from Sen, Brick, and Elliott. We weigh the potential upside and downside of Sen’s suggestion of using machine learning to identify bogus respondents through interactions and improbable combinations of variables. We join Brick in reflecting on bogus respondents’ impact on the state of commercial nonprobability surveys. Finally, we consider Elliott’s discussion of solutions to the challenge raised in our study.
Release date: 2024-06-25

Reference (1,896)

Reference (1,896) (60 to 70 of 1,896 results)

61. Rural Canada Non-Profits Metadata and User Guide, 2020
Surveys and statistical programs – Documentation: 45-20-00042023002
Description: Rural Canada Non-Profits (RCNP) is a database that provides estimates of Non-Profit Organization (NPO) counts, total revenue and total employment in Canada. This document presents the data sources, methods and classification concepts used in the production of the RCNP.
Release date: 2023-03-03
62. The Canadian Consumer Price Index Reference Paper
Surveys and statistical programs – Documentation: 62-553-X
Description:
This Canadian Consumer Price Index (CPI) Reference Paper provides an overview the Canadian CPI. It is intended for a varied audience, ranging from users interested in general information to those requiring more technical or theoretical details. As such, it explains all the important aspects of the Canadian CPI: uses and interpretations, scope, classifications, sample strategy, price collection, index calculation, quality change, weights, basket updates, reliability and uncertainty, special cases and treatments and history.

Release date: 2023-02-20
63. The 2023 Revisions of the Labour Force Survey (LFS)
Surveys and statistical programs – Documentation: 71F0031X2023001
Description: This document introduces and describes updates to the Labour Force Survey estimates in January 2023. These updates include the transition to National Occupational Classification (NOC) 2021 as well as enhancements to the LFS data processing system.
Release date: 2023-01-30
64. Improvements to the Labour Force Survey (LFS)
Surveys and statistical programs – Documentation: 71F0031X
Description:
This paper introduces and explains modifications made to the Labour Force Survey estimates.

Release date: 2023-01-30
65. Persistence and graduation indicators of postsecondary students, 2011/2012 to 2020/2021
Surveys and statistical programs – Documentation: 37-20-00012023001
Description:
This technical reference guide is intended for users of the Education and Labour Market Longitudinal Platform (ELMLP). The data for the products associated with this issue are based on the longitudinal Postsecondary Student Information System (PSIS) administrative data files. Statistics Canada has derived a series of annual indicators of public postsecondary students including persistence rates, graduation rates, and average time to graduation by educational qualification, field of study, age group and gender for Canada, the provinces, and the three combined Territories.

Release date: 2023-01-11
66. Census Content Consultation Guide
Notices and consultations: 92-136-G
Description:
As is the case in advance of each Census, content consultations are being held with data users. The Census Content Consultation Guide gives you the opportunity to provide input.

Release date: 2023-01-09
67. Income Reference Guide, Census of Population, 2021
Surveys and statistical programs – Documentation: 98-500-X2021004
Description: This reference guide provides information to help users effectively use and interpret income data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.
Release date: 2022-12-15
68. Education Reference Guide, Census of Population, 2021
Surveys and statistical programs – Documentation: 98-500-X2021013
Description: This reference guide provides information to help users effectively use and interpret education data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.
Release date: 2022-12-01
69. Census Dictionary
Surveys and statistical programs – Documentation: 98-301-X
Description: The Census Dictionary is a reference document which contains detailed definitions of Census of Population concepts, variables and geographic terms, as well as historical information.
By referring to the Census Dictionary, both beginner and intermediate data users will gain a better understanding of the data and how to compare variables between census years.

The Census Dictionary will be released iteratively starting with geography and non-data dependent topic definitions, tables, figures and appendices with additional content made available based on subsequent topic releases.
Release date: 2022-11-30
70. Guide to the Census of Population
Surveys and statistical programs – Documentation: 98-304-X
Description:
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

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Date modified:: 2024-08-15

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