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Description:

Percentage of enterprises for which specific reasons for purchasing goods or services from unaffiliated foreign businesses were not at all important, somewhat important, important, very important or not applicable, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Reasons for purchasing goods or services from unaffiliated foreign businesses include reduced labour costs, reduced costs other than labour costs, better quality goods or services, no suppliers available in Canada, reduced delivery times, increased access to supply chains or regional trade networks, access to specialized knowledge or technologies, tax or other financial incentives, lack of available labour in Canada, and other reasons for purchasing goods or services from an unaffiliated business outside Canada. Estimates refer to fiscal year 2017 (end date falling after January 1, 2017 and on or before December 31, 2017).

Description:

Percentage of enterprises that exported and did not export goods or services outside Canada, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Enterprises that exported are broken down into exporters with unsuccessful attempts to export to additional markets, and exporters with unsuccessful attempts to export additional goods or services. Enterprises that did not export are broken down into non-exporters with unsuccessful attempts to export.

Description:

Percentage of enterprises that sold goods or services to another business in Canada that then exported these goods or services "as-is", or used the goods as intermediate inputs in a final good that was then exported, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period.

Description:

Percentage of enterprises that had mixed modes of import of goods or services, direct export of goods or services, and sales of goods or services that were then exported "as-is" (indirect exporter) or used as intermediate inputs and then exported (intermediary exporter), by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period.

Description:

Percentage of enterprises for which multinational organizations were among competitors in the main geographical market, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period.

Description:

Percentage of enterprises that introduced product (good or service) innovations that were new to one of their markets, new to this business only, and new to one of their markets and new to this business only, by North American Industry Classification System (NAICS) code and enterprise size, based on a three-year observation period.

Description:

Percentage of enterprises that conducted specific innovation activities, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Innovation activities include research and experimental development; acquisition or development of advanced technology; design activities related to other organizations; employee training specifically for innovation projects; consultation activities with external experts or internal workgroups; activities related to the development and implementation of new marketing methods; market preparation activities directly linked to the introduction of new goods or services; and other innovation activities. Estimates refer to fiscal year 2017 (end date falling after January 1, 2017 and on or before December 31, 2017).

Description:

Percentage of enterprises for which specific reasons for employing personnel outside Canada were not at all important, somewhat important, important, very important or not applicable, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Reasons for employing personnel outside Canada include: reduced labour costs, reduced costs other than labour costs, access to new markets, increased access to supply chains or regional trade networks, increased sales, proximity to important customers, access to specialized knowledge or technologies, tax or other financial incentives, improved logistics, lack of available labour in Canada and other reasons for employing personnel outside Canada. Estimates refer to fiscal year 2017 (end date falling after January 1, 2017 and on or before December 31, 2017).

Description:

Percentage of enterprises that moved activities from outside Canada into Canada, by North American Industry Classification System (NAICS) code and enterprise size, based on a three-year observation period.

Description:

Percentage of enterprises that moved specific business activities from outside Canada into Canada, by North American Industry Classification System (NAICS) code and enterprise size, based on a three-year observation period. Business activities include production of goods, distribution and logistics services, call and help centre services, marketing and sales services, information and communication technology (ICT) services, professional services, engineering and research and development (R&D) services, general management services, and all other business activities.

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.

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.

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); ...).

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; ...).

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: This survey was designed to collect details on topics such as: i) the extent to which graduates of postsecondary programs have been successful in obtaining employment since graduation; ii) the relationship between the graduates' program of study and the employment subsequently obtained; iii) the type of employment obtained and qualification requirements; iv) sources of funding for postsecondary education; and v) government-sponsored student loans and other sources of student debt. The survey results are directed towards policy makers, researchers, educators, employers and persons interested in public postsecondary education and graduates' transition from school to work.

Description:

Freight Rail Services Price Index (FRSPI). Monthly data are available from January 2018. The current base period for the index is 2018=100.

Description:

Freight Rail Services Price Index (FRSPI). Monthly data are available from January 2018. The table presents month-to-month and year-to-year percentage changes for various aggregation levels. The current base period for the index is 2018=100.

Description: Couriers and messengers services price index (CMSPI) by North American Industry Classification System (NAICS). Monthly data are available from January 2010. The table presents data for the most recent reference period and the last four periods. The base period for the index is (2019=100).

Description: Couriers and messengers services price index (CMSPI) by North American Industry Classification System (NAICS). Monthly data are available from February 2010. The table presents month-over-month and year-over-year percentage changes for various aggregation levels. The base period for the index is (2019=100).

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: Kennedy, Mercer, and Lau explore misreporting by respondents in non-probability samples and discover a new feature, namely that of deliberate misreporting of demographic characteristics. This finding suggests that the “arms race” between researchers and those determined to disrupt the practice of social science is not over and researchers need to account for such respondents if using high-quality probability surveys to help reduce error in non-probability samples.

Description: Nonprobability samples are quick and low-cost and have become popular for some types of survey research. Kennedy, Mercer and Lau examine data quality issues associated with opt-in nonprobability samples frequently used in the United States. They show that the estimates from these samples have serious problems that go beyond representativeness. A total survey error perspective is important for evaluating all types of surveys.

Description: Statistical approaches developed for nonprobability samples generally focus on nonrandom selection as the primary reason survey respondents might differ systematically from the target population. Well-established theory states that in these instances, by conditioning on the necessary auxiliary variables, selection can be rendered ignorable and survey estimates will be free of bias. But this logic rests on the assumption that measurement error is nonexistent or small. In this study we test this assumption in two ways. First, we use a large benchmarking study to identify subgroups for which errors in commercial, online nonprobability samples are especially large in ways that are unlikely due to selection effects. Then we present a follow-up study examining one cause of the large errors: bogus responding (i.e., survey answers that are fraudulent, mischievous or otherwise insincere). We find that bogus responding, particularly among respondents identifying as young or Hispanic, is a significant and widespread problem in commercial, online nonprobability samples, at least in the United States. This research highlights the need for statisticians working with commercial nonprobability samples to address bogus responding and issues of representativeness – not just the latter.

Description: This paper is an introduction to the special issue on the use of nonprobability samples featuring three papers that were presented at the 29^th Morris Hansen Lecture by Courtney Kennedy, Yan Li and Jean-François Beaumont.

Description: Using data from the Postsecondary Student Information System (PSIS) and the Census of Population, 2021, this infographic provides information on enrolment in Canadian public postsecondary institutions for transgender and non-binary people.

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.

Description: This fact sheet presents a data ecosystem comprised of a set of data sources that, together, provide information on children eligible for instruction in the minority official language.

Description:

This is a series of fact sheets offering an overview of changes in content for the 2021 Census questionnaire. These include 19 fact sheets focusing on new and modified content and one fact sheet providing information about the design and methodology of the 2019 Census Content Test.

Description:

The Classification of Instructional Programs (CIP) is used for classifying instructional programs according to field of study. CIP was originally created by the National Center for Education Statistics (NCES) in the United States. It is a hierarchical classification. The classification provides a detailed description of each instructional program class together with illustrative examples of the types of instructional programs found in that class. Illustrative examples are also provided of closely related programs that are classified elsewhere. In addition, the classification includes an introduction to CIP and an alternative structure for the aggregation of field of study data. CIP has a ten-year revision cycle.

Description:

This reference guide provides information to help users effectively use and interpret visible minority and population group 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 ethnic or cultural origin 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.