Keyword search

Description: Monthly average retail prices for selected food products, for Canada and provinces. Prices are presented for the current month and the previous four months. Prices are based on transaction data from Canadian retailers, and are presented in Canadian current dollars.

Description:

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

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

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

Description: The international trade monthly interactive dashboard is a comprehensive analytical tool that presents monthly changes in Canada's international merchandise trade data on a balance of payments basis. Four sections are available: 1) a page summarizing the monthly results; 2) a dashboard showing data by product; 3) a dashboard on Canada's principal trading partners; and 4) graphs that show change in price and volume indices on international trade.

Description: The Canadian International Merchandise Trade (CIMT) Web Application offers the most detailed commodity trade data using the Harmonized System (HS) classification of goods (the 8-digit commodity level for exports and the 10-digit for imports). The CIMT Web Application also offers data at the international 6-digit commodity level. With the CIMT Web Application the user can visualize the latest information on customs based monthly trade through tables and charts as well as a time series report. For a selected period of time, one can also customize its selection and visualize trade, export or import, data for a specific trading partner, a specific province and a specific variable such as value, volume and a percentage change on a monthly or annual basis. The application has also the ability to retrieve the top 25 commodities traded between a selected by the user geography, Canada or a province, and trading partner, the World or a specific country, for the month of interest. When desired, the user can copy the data seen on the screen into their preferred data manipulation software.

Description: This interactive dashboard provides access to current and historical average price data for selected food products in a dynamic and customizable format. The price data is available for Canada and the provinces. Prices are based on transaction data from Canadian retailers, and are presented in Canadian current dollars.

This web-based application is updated monthly, as soon as the data for the latest reference month is released in The Daily.

Description: This table contains 107 series, with data starting from 1946 (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 items: Canada ...), Government of Canada direct securities and loans (107 items: Classification by type of issue; total outstanding; Total; direct securities outstanding; Treasury Bills; Guaranteed securities ...).

Description:

Canada and United States bilateral trade in goods data produced by Statistics Canada and the United States Census Bureau (customs basis) and the United States Bureau of Economic Analysis (balance of payments basis). Data are presented before and after adjustments made to standardize definitions. Quarterly data are available on Customs and on Balance of payments basis and are not seasonally adjusted.

Description: International merchandise trade data grouped by Principal Trading Partners (PTP). Users have the option of selecting Imports, Exports, or Trade Balance. Data are unadjusted and seasonally adjusted, and are on a Customs and Balance of Payments basis.

Description:

The "Profiles" series provides a statistical overview of various census geographic areas. Part A provides basic demographic, mother tongue, dwelling, household and family data collected from all households, that is, on a 100% basis. Part B provides data collected from a 20% sample of households on characteristics such as home language, ethnic origin, place of birth, education, religion, labour force activity, housing costs and income.

Description:

The objectives of this survey were:- to accurately describe the nature of child care needs in Canada;

- to find out what child care arrangements and options parents prefer;- to find out what influences child care needs, use patterns and preferences;- to examine how different child care patterns affect children, and parents, both on an individual basis and in relationship to each other;- to find out how parents feel about the affordability and quality of major child care options.

This is a personal computer version with the data residing in a relational database along with retrieval software.

Description:

The objective of this survey is to:- measure the frequency and number of job changes occurring in the Canadian labour market over one-two-and three year periods;- provide information on the characteristics of jobs held (wage rates, usual work schedules, etc.);- identify groups of people who would benefit from EIC programs;- identify participants of specific EIC programs.

Both cross-sectional (annual) files as well as longitudinal files are available as separate computer (main frame) tapes or together on a Compact Disk.

Description:

The "Profiles" series provides a statistical overview of various census geographic areas. Part A provides basic demographic, mother tongue, dwelling, household and family data collected from all households, that is, on a 100% basis.

Description:

The "Profiles" series provides a statistical overview of various census geographic areas. Part A provides basic demographic, mother tongue, dwelling, household and family data collected from all households, that is, on a 100% basis.

Description:

The "Profiles" series provides a statistical overview of various census geographic areas. Part A provides basic demographic, mother tongue, dwelling, household and family data collected from all households, that is, on a 100% basis.

Description:

This study compares the earnings of bilingual and unilingual workers in three urban centres: Montreal, Toronto and Ottawa-Hull. Differences in the earnings of bilingual and unilingual workers are considered in the light of several demographic and job-related traits.

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: This discussion summarizes the interesting new findings around measurement errors in opt-in surveys by Kennedy, Mercer and Lau (KML). While KML enlighten readers about “bogus responding” and possible patterns in them, this discussion suggests combining these new-found results with other avenues of research in nonprobability sampling, such as improvement of representativeness.

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.

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.

Description: This product contains boundary files and user documentation for environmental analysis using geographical information systems (GIS).

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.

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.

Description: This electronic publication presents the methodology underlying the production of the life tables for Canada, provinces and territories.

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.

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.

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.

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.