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All (24,388)

All (24,388) (40 to 50 of 24,388 results)

  • 41. Economic dependency profile of tax filers by source of income and sex
    Table: 11-10-0033-01
    Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
    Frequency: Annual
    Description: Individuals; Economic dependency profile of tax filers by source of income and sex (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 42. Tax filers and dependants with income by sex, income taxes, selected deductions and benefits
    Table: 11-10-0034-01
    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 with income by sex, income taxes, selected deductions and benefits (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 43. Tax filers and dependants, seniors with income by source of income and age
    Table: 11-10-0039-01
    Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
    Frequency: Annual
    Description: Seniors and individuals; Tax filers and dependants, seniors with income by source of income and age groups (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 44. Tax filers and dependants with income by after-tax income, sex and age
    Table: 11-10-0050-01
    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 with income by after-tax income, sex and age groups (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 45. Tax filers and dependants with income by total income, income taxes paid and after-tax income, sex and age
    Table: 11-10-0051-01
    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 with income by total income, income taxes paid and after-tax income, sex and age groups (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 46. Tax filers and dependants with dividend and interest income by sex and age group
    Table: 11-10-0067-01
    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 with dividend and interest income by sex and age group (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 47. Tax filers and dependants with dividend and interest income by sex and income group
    Table: 11-10-0068-01
    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 with dividend and interest income by sex and income group (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 48. Census families with dividend and interest income by family type
    Table: 11-10-0069-01
    Geography: Canada, Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
    Frequency: Annual
    Description:

    Families of tax filers; Census families with dividend and interest income by family type (final T1 Family File; T1FF).

    Release date: 2024-06-27
  • 49. Tax filers and dependants with capital gains by sex and income group
    Table: 11-10-0070-01
    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 with capital gains by sex and income group (final T1 Family File; T1FF).
    Release date: 2024-06-27
  • 50. Census families with capital gains by family type
    Table: 11-10-0071-01
    Geography: Canada, Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
    Frequency: Annual
    Description:

    Families of tax filers; Census families with capital gains by family type (final T1 Family File; T1FF).

    Release date: 2024-06-27
Data (12,031)

Data (12,031) (0 to 10 of 12,031 results)

  • 1. 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
  • 2. 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
  • 3. 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
  • 4. 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
  • 5. 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
  • 6. 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
  • 7. Earnings and payroll employment in brief: Interactive app
    Data Visualization: 14-20-00012019001
    Description: This interactive visualization application provides a comprehensive picture of the Canadian labour market using the most recent data from the Survey of Employment, Payrolls and Hours (SEPH). The estimates are seasonally adjusted and available by province and largest industrial sector. Historical estimates, going back 10 years, are also included. The interactive application allows users to quickly and easily explore and personalize the information presented. Combine multiple provinces and industrial sectors to create your own labour market domains of interest.
    Release date: 2024-06-27
  • 8. Canadian Labour Market Observatory
    Data Visualization: 14-20-0001
    Description:

    The Canadian Labour Market Observatory consists of interactive data visualization applications showcasing the vast amount of publicly available labour market information. The fully interactive applications allow Canadians to quickly and easily personalize the information in a way that is relevant to them and their interests.

    Release date: 2024-06-27
  • 9. Statistics Canada - Data Visualization Products
    Table: 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: 2024-06-27
  • 10. Funds advanced, outstanding balances, and interest rates for new and existing lending, Bank of Canada
    Table: 10-10-0006-01
    Geography: Canada
    Frequency: Monthly
    Description:

    This table contains 102 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 (2 items: Dollars; Interest rate). 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
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) (0 to 10 of 1,892 results)

  • 1. 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
  • 2. Technical Reference Guide for the Annual Income Estimates for Census Families, Individuals and Seniors, T1 Family File
    Surveys and statistical programs – Documentation: 72-212-X
    Description: Data on income of census families, individuals and seniors are derived from income tax returns. The data for the products associated with this release are derived from the T1 file that Statistics Canada receives from Canada Revenue Agency (CRA) thirteen months after the end of the taxation year.
    Release date: 2024-06-27
  • 3. Census Subdivision Boundary File, Reference Guide
    Geographic files and documentation: 92-162-G
    Description: This reference guide is intended for users of the Census Subdivisions Boundary File. The guide provides an overview of the file, the general methodology used to create it, and important technical information for users.
    Release date: 2024-06-26
  • 4. Census Subdivision Boundary File
    Geographic files and documentation: 92-162-X
    Description: The Census Subdivision Boundary File contains the boundaries of all census subdivisions which combined cover all of Canada. A census subdivision is a municipality or an area treated as an equivalent to a municipality for statistical purposes (for example, Indian reserves and unorganized territories). The file provides a framework for mapping and spatial analysis using commercially available geographic information systems (GIS) or other mapping software.

    The Census Subdivision Boundary File is portrayed in Lambert conformal conic projection and is based on the North American Datum of 1983 (NAD83). A reference guide is available (92-162-G).

    Release date: 2024-06-26
  • 5. Road Network File, Reference Guide
    Geographic files and documentation: 92-500-G
    Description: This reference guide is intended for users of the Road Network File. The guide provides an overview of the file, the general methodology used to create it, and important technical information for users.
    Release date: 2024-06-26
  • 6. Road Network File
    Geographic files and documentation: 92-500-X
    Geography: Canada
    Description: The Road Network File (RNF) is a digital representation of Canada's national road network, containing information such as street names, types, directions and address ranges. The information comes from the National Geographic Database (NGD).

    A reference guide is available (92-500-G).

    Release date: 2024-06-26
  • 7. Interim List of Changes to Municipal Boundaries, Status, and Names
    Notices and consultations: 92F0009X
    Description: This report provides a summary of changes to municipal boundaries, status and names. The list is usually produced on an annual basis for changes that occurred during the previous year. A five year list is produced on Census of population years.
    Release date: 2024-06-26
  • 8. Population Projections for Canada, Provinces and Territories: Technical Report on Methodology and Assumptions
    Surveys and statistical programs – Documentation: 91-620-X
    Description: This report aims to describe the methods used for the calculation of projection parameters, the various projection assumptions and their rationales.
    Release date: 2024-06-24
  • 9. Guide to the Job Vacancy and Wage Survey, 2024
    Surveys and statistical programs – Documentation: 75-514-G2024001
    Description: The Guide to the Job Vacancy and Wage Survey contains a dictionary of concepts and definitions, and covers topics such as survey methodology, data collection, processing, and data quality.
    Release date: 2024-06-18
  • 10. Guide to the Job Vacancy and Wage Survey
    Surveys and statistical programs – Documentation: 75-514-G
    Description: The Guide to the Job Vacancy and Wage Survey contains a dictionary of concepts and definitions, and covers topics such as survey methodology, data collection, processing, and data quality. The guide covers both components of the survey: the job vacancy component, which is quarterly, and the wage component, which is annual.
    Release date: 2024-06-18
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