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Description: This table contains 92 series, with data starting from 2009 (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) Sector (92 items: Total, industries and households; Total, industries; Crop production; Animal production; ...).

Description: This video is part of a series that is designed to give you a basic understanding of the Census of Population web pages. This video will provide an overview of the major links and products on the main page that are available to all users.

Description: This video is part of a series that is designed to give you a basic understanding of the Census of Population web pages. The purpose of this video is to explain where to find the most popular standard data product of the Census of Population, the 2021 Census Profile, and how to filter the data.

Description: This video is part of a series that is designed to give you a basic understanding of the Census of Population web pages. The purpose of this video is to explain how to add geographies in the 2021 Census Profile and to present the various downloading options to see the data.

Description: Once every five years, the Census of Population provides a detailed and comprehensive statistical portrait of Canada that is vital to our country. It is the primary source of sociodemographic data for specific population groups such as lone-parent families, Indigenous peoples, immigrants, seniors and language groups.

In order to help users of census products to better understand the various Census of Population concepts, Statistics Canada has developed, in the context of the activities of the 2021 Census and previous censuses, a collection of short videos. These videos are a reference source for users who are new to census concepts or those who have some experience with these concepts, but may need a refresher or would like to expand their knowledge.

Description: Farm input price index (FIPI). Quarterly data are available from from the first quarter of 2002. The table presents data for the most recent reference period and the last four periods. The base period for the index is (2012=100).

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Farm input price index (FIPI). Data are available from from the second quarter of 2002. The table presents data for the most recent reference period and the last four periods. The base period for the index is (2012=100).

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Weekly Itinerant aircraft movements (domestic, transborder and international), total of all Canadian airports with NAV CANADA towers.

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The table is part of Frontier Counts. The data comes from the Primary Inspections Kiosks (PIK), from the Canada Border Services Agency (CBSA). Keywords include: airport, arrival, entry, excursionist, overnight, plane, port of entry, same-day, tourism, tourist, travel and visit.

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The table is part of Frontier Counts. The data comes from the Integrated Primary Inspection Line (IPIL), from the Canada Border Services Agency (CBSA). Keywords include: arrival, automobile, car, entry, excursionist, motorcycle, overnight, port of entry, same-day, tourism, tourist, travel and visit.

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Electric power selling price index (EPSPI). Monthly data are available from February 1981. The table presents month-over-month and year-over-year percentage changes for various aggregation levels. The base period for the index is (2014=100).

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This table contains 661 series, with data starting from 1981 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (19 items: Canada, provinces and international; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...) ; Assets and liabilities (36 items: Bank notes and coin other than gold and silver bullion; Securities issued or guaranteed by a Canadian province; Securities issued or guaranteed by a Canadian municipal or school corporation; Other securities; ...).

Description: This table provides manufacturing sales data based on origin, destination and industry cross-tabulations from the Annual Survey of Manufacturing and Logging. Origins include all provinces and territories. Destinations include all provinces and territories, the United States of America, and the rest of the world. Industry detail is available at the 2, 3 and 4 digit NAICS level.

Description: Historical (real-time) releases of the measures of core inflation, with data from 1989 (not all combinations necessarily have data for all years). Data are presented for the current release and previous four releases. Users can select other releases that are of interest to them.

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Retail sales, by commodities classified under the North American Product Classification System (NAPCS) Canada 2022 and by North American Industry Classification System (NAICS) 2022, quarterly, Canada.

Description: Retail sales, by commodities classified under the North American Product Classification System (NAPCS) Canada 2022, monthly, Canada.

Description: Historical releases of retail trade sales, available for all members under release and adjustment dimensions, for Canada, provinces and territories, available on a monthly basis in dollars x 1,000.

Description: Historical (real-time) releases of retail sales, price, and volume, available for all members under North American Industry Classification System (NAICS) dimension, for Canada, available on a monthly basis, seasonally adjusted, in dollars x 1,000,000.

Description: This table contains 29 series, with data starting from 1953 (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), Assets and liabilities (29 items: Total assets; Total, Government of Canada, direct and guaranteed securities; Government of Canada, Treasury Bills; Total, Government of Canada, bonds; ...).

Description:

This interactive visualization application provides a comprehensive picture of the Canadian labour market using the most recent Labour Force Survey data available. The estimates are seasonally adjusted and available by province, sex, age group and industry. Historical estimates, going back 5 years, are also included for monthly employment changes and unemployment rates. The interactive application allows users to quickly and easily explore and personalize the information presented. Combine multiple provinces, sexes and age groups to create your own labour market domains of interest.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

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.

Description: We provide comparisons among three parametric methods for the estimation of participation probabilities and some brief comments on homogeneous groups and post-stratification.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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. 

Description:

This guide focuses on the following topic: education. This reference guide provides information that enables users to effectively use, apply and interpret data from the 2016 Census. This guide contains definitions and explanations of concepts, classifications, data quality and comparability to other sources. Additional information is included for specific variables to help general users better understand the concepts and questions used in the census.

Description:

This reference guide provides information to help users effectively use and interpret language 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.

Description: This reference guide provides information to help users effectively use and interpret commuting 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.

Description: This reference guide provides information to help users effectively use and interpret labour 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.

Description: This reference guide provides information to help users effectively use and interpret instruction in the minority official language 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.