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All (24,388)

All (24,388) (0 to 10 of 24,388 results)

  • 1. Payroll employment, earnings and hours, and job vacancies April 2024
    Stats in brief: 11-001-X20241793555
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-06-27
  • 2. Principal field crop areas June 2024
    Stats in brief: 11-001-X20241794822
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-06-27
  • 3. Income of men and women, sub-provincial regions, T1 Family File: Interactive tool
    Data Visualization: 71-607-X2019006
    Description:

    This interactive tool allows users to visualize income data of tax filers and their dependants by sex and age for Canada, provinces/territories and census metropolitan area/census agglomeration. It shows the most recent data available from the Annual income estimates for Census families and individuals (T1 Family file).

    Release date: 2024-06-27
  • 4. Sources of family income by family type, sub-provincial regions, T1 Family File: Interactive tool
    Data Visualization: 71-607-X2019007
    Description:

    This interactive tool allows users to visualize income data of census families and persons not in census families by type of family and income source for Canada, provinces/territories and census metropolitan area/census agglomeration. It shows the most recent data available from the Annual income estimates for Census families and individuals (T1 Family file). For the national and provincial levels, some data are presented from the year 2000 and onward.

    Release date: 2024-06-27
  • 5. 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: 2024-06-27
  • 6. National Culture Indicators: Interactive tool
    Data Visualization: 71-607-X2022011
    Description: The National Culture Indicators Dashboard is an interactive tool that provides access to current and historical quarterly data on culture and sport Gross Domestic Product (GDP), output and jobs. The National Culture Indicators are an extension of the Provincial and Territorial Culture Satellite Account and the Provincial and Territorial Culture Indicators. The tool allows users to compare data on culture and sport, in Canada, by domains and subdomains.
    Release date: 2024-06-27
  • 7. Aviation Data Visualization Hub: Monthly Civil Aviation Indicators
    Data Visualization: 71-607-X2024006
    Description: This data visualization dashboard provides information on the main financial and operational data from Canadian Level I air carriers in an interactive format. The dashboard features information on passengers, load factor, passenger-kilometres, available seat kilometres, hours flown, turbo fuel consumed, and total operating revenue.
    Release date: 2024-06-27
  • 8. Aviation Data Visualization Hub: Aircraft Movements
    Data Visualization: 71-607-X2024007
    Description: This data visualization dashboard provides data on aircraft movements at Canada's major airports and select small airports in an interactive format. It allows users to compare aircraft movements by geography, class of operation, type of operation, sector (domestic, transborder and other international) and the busiest airports by amount of aircraft activity.
    Release date: 2024-06-27
  • 9. T1 Family File, Final Estimates, 2022
    Surveys and statistical programs – Documentation: 72-212-X2024001
    Description: Data on income of census families, individuals and seniors are derived from the T1 Family File (T1FF). This file is based on information from the T1 form, Income Tax and Benefit Return, which Statistics Canada receives from Canada Revenue Agency (CRA) thirteen months after the end of the taxation year.
    Release date: 2024-06-27
  • 10. Earnings and Wages – A guide to using indicators from the Survey of Employment, Payrolls and Hours and the Labour Force Survey
    Articles and reports: 75-005-M2024002
    Description: Survey of Employment, Payrolls and Hours (SEPH) and the Labour Force Survey (LFS) each provide monthly indicators of pay received by employees. Year-over-year variations in average weekly earnings (from SEPH) and average hourly wages (from LFS) provide information on current wage dynamics. This guide provides information to help analysts use each indicator by highlighting their key conceptual and measurement differences. It also outlines possible causes of variations for each indicator and provides general examples of using both measures.
    Release date: 2024-06-27
Data (12,031)

Data (12,031) (10 to 20 of 12,031 results)

  • 11. Funds advanced, outstanding balances, and interest rates for new and existing lending, dollars, Bank of Canada
    Table: 10-10-0006-02
    Geography: Canada
    Frequency: Monthly
    Description:

    This table contains 51 series, with data starting from 2013, and some select series starting from 2016. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada), Components (51 items: Total, funds advanced, residential mortgages, insured; Variable rate, insured; Fixed rate, insured, less than 1 year; Fixed rate, insured, from 1 to less than 3 years; ...), and Unit of measure (1 item: Dollars). For additional clarification on the component dimension, please visit the OSFI website for the Report on New and Existing Lending.

    Release date: 2024-06-27
  • 12. 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: 2024-06-27
  • 13. 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: 2024-06-27
  • 14. Selected characteristics of tax filers and dependants, income and demographics (final T1 Family File)
    Table: 11-10-0004-01
    Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
    Frequency: Annual
    Description: Individuals; Tax filers and dependants, summary table, income and demographics (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 15. Tax filers and dependants by sex, marital status and age
    Table: 11-10-0005-01
    Geography: Canada, Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
    Frequency: Annual
    Description: Individuals; Tax filers and dependants by sex, marital status and age groups (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 16. Tax filers and dependants by single years of age
    Table: 11-10-0006-01
    Geography: Canada, Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
    Frequency: Annual
    Description: Individuals; Tax filers and dependants by sex and single years of age (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 17. Tax filers and dependants with income by source of income
    Table: 11-10-0007-01
    Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
    Frequency: Annual
    Description: Individuals; Tax filers and dependants with income by source of income (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 18. Tax filers and dependants with income by total income, sex and age
    Table: 11-10-0008-01
    Geography: Canada, Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
    Frequency: Annual
    Description: Individuals; Tax filers and dependants by total income, sex and age groups (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 19. Selected income characteristics of census families by family type
    Table: 11-10-0009-01
    Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
    Frequency: Annual
    Description: Families of tax filers; Selected income characteristics of census families by family type (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 20. Tax filers and dependants by census family type and age
    Table: 11-10-0010-01
    Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
    Frequency: Annual
    Description: Individuals; Tax filers and dependants by census family type and age groups (final T1 Family File; T1FF).
    Release date: 2024-06-27
Analysis (9,991)

Analysis (9,991) (10 to 20 of 9,991 results)

  • 11. Economic and Social Reports June 2024
    Stats in brief: 11-001-X202417822588
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-06-26
  • 12. Weekly aircraft movements June 8 to 14, 2024
    Stats in brief: 11-001-X202417823765
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-06-26
  • 13. 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
  • 14. Economic and Social Reports
    Journals and periodicals: 36-28-0001
    Description: Economic and Social Reports includes in-depth research, brief analyses, and current economic updates on a variety of topics, such as labour, immigration, education and skills, income mobility, well-being, aging, firm dynamics, productivity, economic transitions, and economic geography. All the papers are institutionally reviewed and the research and analytical papers undergo peer review to ensure that they conform to Statistics Canada's mandate as a governmental statistical agency and adhere to generally accepted standards of good professional practice.
    Release date: 2024-06-26
  • 15. 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
  • 16. 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
  • 17. 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
  • 18. 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
  • 19. 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
  • 20. 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
Reference (1,892)

Reference (1,892) (40 to 50 of 1,892 results)

  • 41. Labour Force Survey Response Rates, September 2023
    Surveys and statistical programs – Documentation: 75-005-M2023001
    Description: This document provides information on the evolution of response rates for the Labour Force Survey (LFS) and a discussion of the evaluation of two aspects of data quality that ensure the LFS estimates continue providing an accurate portrait of the Canadian labour market.
    Release date: 2023-10-30
  • 42. Contiguously Settled Areas: Boundaries and User Documentation
    Geographic files and documentation: 16-510-X2023001
    Description: This product contains contiguously settled area (CSA) boundaries for a subset of Canadian population centres for 2010 and 2020 with user documentation. The CSA boundaries are derived from land cover data and represent the geographic extent of settled areas based on their physical footprint on the landscape. The boundaries can be used for reference, mapping and spatial analysis of settled areas and urban ecosystems. The CSA boundaries are created and maintained under the umbrella of the Census of Environment, and will support Statistics Canada's ecosystem accounting efforts.
    Release date: 2023-10-27
  • 43. Environmental Statistics: Boundary Files
    Geographic files and documentation: 16-510-X
    Description: This product contains boundary files and user documentation for environmental analysis using geographical information systems (GIS).
    Release date: 2023-10-27
  • 44. User Guide for the Survey of Household Spending, 2021
    Surveys and statistical programs – Documentation: 62F0026M2023001
    Description: This guide presents information of interest to users of data from the Survey of Household Spending (SHS). It includes descriptions of the survey terms and variables definitions as well as of the survey methodology and data quality. The guide also includes a section describing various examples of estimates that can be drawn from the survey data.
    Release date: 2023-10-18
  • 45. Sampling and Weighting Technical Report, Census of Population
    Surveys and statistical programs – Documentation: 98-306-X
    Description:

    This report describes sampling, weighting and estimation procedures used in the Census of Population. It provides operational and theoretical justifications for them, and presents the results of the evaluations of these procedures.

    Release date: 2023-10-04
  • 46. Methods for Constructing Life Tables for Canada, Provinces and Territories
    Surveys and statistical programs – Documentation: 84-538-X
    Geography: Canada
    Description: This electronic publication presents the methodology underlying the production of the life tables for Canada, provinces and territories.
    Release date: 2023-08-28
  • 47. Agriculture–Population Linkage: Data quality report
    Surveys and statistical programs – Documentation: 32-26-0006
    Description: This report provides data quality information pertaining to the Agriculture–Population Linkage, such as sources of error, matching process, response rates, imputation rates, sampling, weighting, disclosure control methods and data quality indicators.
    Release date: 2023-08-25
  • 48. T1 Family File, Final Estimates, 2021
    Surveys and statistical programs – Documentation: 72-212-X2023001
    Description: Data on income of census families, individuals and seniors are derived from the T1 Family File (T1FF). This file is based on information from the T1 form, Income Tax and Benefit Return, which Statistics Canada receives from Canada Revenue Agency (CRA) thirteen months after the end of the taxation year.
    Release date: 2023-07-12
  • 49. Place of Birth, Generation Status, Citizenship and Immigration Reference Guide, Census of Population, 2021
    Surveys and statistical programs – Documentation: 98-500-X2021007
    Description:

    This reference guide provides information to help users effectively use and interpret place of birth, generation status, citizenship and immigration 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: 2023-06-21
  • 50. Census of Population Reference Guide
    Surveys and statistical programs – Documentation: 98-500-X
    Description:

    Provides information that enables users to effectively use, apply and interpret data from the Census of Population. Each guide contains definitions and explanations on census concepts as well as a data quality and historical comparability section. Additional information will be included for specific variables to help users better understand the concepts and questions used in the census.

    Release date: 2023-06-21
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