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Description: This table contains 7 series, with data starting from 1972 (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), Commodity (7 items: Total, all commodities; Total excluding energy; Energy; Metals and Minerals; ...).

Description:

This table contains 27 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 (1 item: Canada); Type of currency (27 items: Australian dollar, daily average; Brazilian real, daily average; Chinese renminbi, daily average; European euro, daily average; ...).

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

Description: This web application provides access to Statistics Canada’s Labour Market Indicators for Canada, by province and by census metropolitan area. This dynamic application allows users to view geographical rankings for each labour market indicator and to create quick and easy reports with interactive maps and charts that can be easily copied into other programs. All provincial and CMA estimates used in this application are seasonally adjusted, 3-month moving averages. Labour Force Survey data at the provincial level published each month in The Daily are seasonally adjusted monthly estimates.

Description: This web application provides access to Statistics Canada’s Labour Market Indicators for Canada, by province, territory and economic region (ER). This dynamic application allows users to view a snapshot of key labour market indicators, observe geographical rankings for each indicator using an interactive map and table, and easily copy data into other programs. The provincial and ER estimates used in this application from the Labour Force Survey (LFS) are three-month moving averages, unadjusted for seasonality. The provincial, territorial and ER estimates used in this application from the Job Vacancy and Wage Survey (JVWS) are quarterly data, unadjusted for seasonality. Historical estimates are available in this application, with data going back 10 years for the LFS and from the first quarter of 2016 for JVWS.

Description: The need for alternative data sources is of growing importance for both supplementing Statistics Canada's data holdings and for nowcasting economic activity. In response to this need, Statistics Canada initiated the development of a Real-time Local Business Conditions Index (RT-LBCI). The index brings together data from a few different sources, including Google's Places API (containing data on temporary and permanent businesses closures), TomTom Real-time traffic API (road traffic data), as well as information from Statistics Canada data holdings (monthly retail and wholesale, Business Register, etc.). The project aims to compute a near real-time index of economic activity in Canadian major cities.

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: Number of persons in the labour force (employment and unemployment) and not in the labour force, unemployment rate, participation rate, and employment rate, by sex and detailed age group, last 5 months.

Description: Number of persons in the labour force (employment and unemployment) and not in the labour force, unemployment rate, participation rate, and employment rate, by sex and detailed age group. Data are presented for 24 months earlier, 12 months earlier and current month, as well as 24-month and year-over-year level change and percentage change.

Description: Number of persons in the labour force (employment and unemployment) and not in the labour force, unemployment rate, participation rate, and employment rate, by educational attainment, sex and age group, last 5 months.

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

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

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.

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: This product contains articles related to the latest methodological, conceptual developments in the Canadian System of Macroeconomic Accounts as well as the analysis of the Canadian economy. It includes articles detailing new methods, concepts and statistical techniques used to compile the Canadian System of Macroeconomic Accounts. It also includes information related to new or expanded data products, provides updates and supplements to information found in various guides and analytical articles touching upon a broad range of topics related to the Canadian economy.

Description: From November 2022 to March 2023 Statistics Canada undertook a series of discussions to obtain feedback on the questions used to identify First Nations people, Métis and Inuit on the Census of Population and on other Statistics Canada surveys. This report summarizes the feedback received during these discussions.

Description: Engagement on the questions used to identify First Nations people, Métis and Inuit that are included on the Census of Population and on other Statistics Canada surveys is an important part of ensuring high quality and meaningful data are collected. The feedback received during these discussions are presented in these reports.

Description: This classification system was developed conjointly by the Social Sciences and Humanities Research Council of Canada (SSHRC), the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Foundation for Innovation (CFI), the Canadian Institutes of Health Research (CIHR), and Statistics Canada which is the custodian. This shared standard classification, inspired by the Frascati Model 2015 of the Organisation for Economic Co-operation and Development (OECD), will be used by the federal granting agencies and Statistics Canada to collect, and disseminate data related to research and development in Canada. The Canadian Research and Development Classification (CRDC) first official version was the 2020 Version 1.0, now being replaced by CRDC Version 2.0. The CRDC is revised within 2 years for minor changes, and every five years for major revisions. CRDC 2020 Version 2.0 is composed of 3 main pieces: the type of activity or TOA (with 3 categories), the field of research or FOR (with 1,671 fields at the lowest level) and socioeconomic objective or SEO (with 85 main groups at the lowest level).

Description: These reference guides are intended for users of the Education and Labour Market Longitudinal Platform (ELMLP). The guide provides an overview of the Postsecondary Student Information System (PSIS) and the Registered Apprenticeship Information System (RAIS), the general methodology used to create longitudinal indicators, and important technical information for users.

Description: User consultation is the first step in determining Census Program content. The findings of content consultations are presented in these reports.

Description: Data from the Census of Population are important for all communities and are vital to plan services that support education, employment, transportation, health care and housing. To maintain the relevance of the census, Statistics Canada evaluates and reviews the census questionnaire content for each census cycle. In preparation for the 2026 Census, Statistics Canada consulted Canadians from fall 2022 to spring 2023. Detailed responses were received from organizations and individuals representing federal, provincial, territorial and local government departments; First Nations people, Métis and Inuit; the general public; academia; special interest groups; and the private sector.

This report focuses on the findings of the 2026 Census data needs consultation and stakeholder discussions. Chapter 1 explains whom we consulted. Chapter 2 describes the strength of census data users’ needs such as the size of the population of interest. Chapter 3 provides an assessment of the perceived data gaps in census content and the availability and suitability of alternative data sources. Chapter 4 focuses on information needs by census topic and how preparations for the 2024 Census Test will help meet these needs.

Description: The Guide to the Survey of Employment, Payrolls and Hours contains a dictionary of concepts and definitions and covers topics such as survey methodology, data collection and processing, and data quality. It also provides information on products and services, as well as the survey questionnaire.

Description: This handbook complements the tables of the Pan-Canadian Education Indicators Program (PCEIP). It is a guide that provides general descriptions for each indicator and indicator component. PCEIP has five broad indicator sets: a portrait of the school-age population; financing education systems; elementary and secondary education; postsecondary education; and transitions and outcomes.

The Pan-Canadian Education Indicators Program (PCEIP) is a joint venture of Statistics Canada and the Council of Ministers of Education, Canada.

Description: Health regions are defined by the provinces and represent administrative areas or regions of interest to health authorities. This product contains correspondence files (linking health regions to latest Census geographic codes) and digital boundary files. User documentation provides an overview of health regions, sources, methods, limitations and product description (file format and layout).

In addition to the geographic files, this product also includes Census data (basic profile) for health regions.