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Description: This infographic uses administrative tax data to provide a visual representation of non-financial co-operatives in Canada in 2022. Presented data includes counts of co-operatives at the national and provincial levels, as well as financial and employment statistics.

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

Description: Every year, Statistics Canada collects data from hundreds of surveys. As the amount of data gathered increases, Statistics Canada has introduced infographics to help people, business owners, academics, and management at all levels, understand key information derived from the data. Infographics can be used to quickly communicate a message, to simplify the presentation of large amounts of data, to see data patterns and relationships, and to monitor changes in variables over time.

These infographics will provide a quick overview of Statistics Canada survey data.

Description: Lumber, monthly production, shipments and stocks by species; data in thousands of cubic metres.

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Lumber, monthly production, by product; data in thousands of cubic metres.

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Lumber, monthly shipments, by product; data in thousands of cubic metres.

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Lumber, monthly stocks, by product; data in thousands of cubic metres.

Description: Number of hours in a standard work week for salaried employees, by North American Industry Classification System (NAICS), last 5 months.

Description: Fixed weighted index (2002=100) of average hourly earnings for all employees, by North American Industry Classification System (NAICS), last 5 months.

Description: Number of employees and average weekly earnings (including overtime) for all employees by North American Industry Classification System (NAICS), last 5 months.

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Number of employees and average weekly earnings (including overtime) for all employees in the automotive industry, based on the North American Industry Classification System (NAICS), last 5 months.

Description: Number of employees, average hourly and weekly earnings, and average weekly hours by North American Industry Classification System (NAICS) and type of employee, last 5 months.

Description: Number of employees, average hourly and weekly earnings (including overtime), and average weekly hours for the industrial aggregate excluding unclassified businesses, last 5 months.

Description: Number of employees and average weekly earnings (including overtime) for all employees by provinces, territories and North American Industry Classification System (NAICS), last 5 months.

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Average weekly hours for employees paid by the hour, by North American Industry Classification System (NAICS) and overtime status, last 5 months.

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Major wage settlements, including number of agreements, number of employees, average duration of agreements, first year average percentage wage adjustment, and annual average percentage wage adjustment, by jurisdiction, industry, sector, and cost of living adjustment (COLA), monthly, from 1977 to 2020.

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Major wage settlements, including number of agreements, number of employees, average duration of agreements, first year average percentage wage adjustment, and annual average percentage wage adjustment, by jurisdiction, industry, sector, and cost of living adjustment (COLA), quarterly, from 1977 to 2020.

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Nearly all surveys and censuses are subject to two types of nonresponse: unit (total) and item (partial). Several methods of compensating for nonresponse have been developed in an attempt to reduce the bias associated with nonresponse. This paper summarizes the nonresponse adjustment procedures used at the U.S. Census Bureau, focusing on unit nonresponse. Some discussion of current and future research in this area is also included.

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From an annual sample of U.S. corporate tax returns, the U.S. Internal Revenue Service provides estimates of population and subpopulation totals for several hundred financial items. The basic sample design is highly stratified and fairly complex. Starting with the 1981 and 1982 samples, the design was altered to include a double sampling procedure. This was motivated by the need for better allocation of resources, in an environment of shrinking budgets. Items not observed in the subsample are predicted, using a modified hot deck imputation procedure. The present paper describes the design, estimation, and evaluation of the effects of the new procedure.

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The Canadian Census of Construction (COC) uses a complex plan for sampling small businesses (those having a gross income of less than $750,000). Stratified samples are drawn from overlapping frames. Two subsamples are selected independently from one of the samples, and more detailed information is collected on the businesses in the subsamples. There are two possible methods of estimating totals for the variables collected in the subsamples. The first approach is to determine weights based on sampling rates. A number of different weights must be used. The second approach is to impute values to the businesses included in the sample but not in the subsamples. This approach creates a complete “rectangular” sample file, and a single weight may then be used to produce estimates for the population. This “large-scale imputation” technique is presently applied for the Census of Construction. The purpose of the study is to compare the figures obtained using various estimation techniques with the estimates produced by means of large-scale imputation.

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In the presence of unit nonresponse, two types of variables can sometimes be observed for units in the “intended” sample s, namely, (a) variables used to estimate the response mechanism (the response probabilities), (b) variables (here called co-variates) that explain the variable of interest, in the usual regression theory sense. This paper, based on Särndal and Swensson (1985 a, b), discusses nonresponse adjusted estimators with and without explicit involvement of co-variates. We conclude that the presence of strong co-variates in an estimator induces several favourable properties. Among other things, estimators making use of co-variates are considerably more resistant to nonresponse bias. We discuss the calculation of standard error and valid confidence intervals for estimators involving co-variates. The structure of the standard error is examined and discussed.

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The procedure of subsampling the nonrespondents suggested by Hansen and Hurwitz (1946) is considered. Post-stratification prior to the subsampling is examined. For the mean of a characteristic of interest, ratio estimators suitable for different practical situations are proposed and their merits are examined. Suitable ratio estimators are also suggested for the situations in which the Hard-Core are present.

Description:

Missing survey data occur because of total nonresponse and item nonresponse. The standard way to attempt to compensate for total nonresponse is by some form of weighting adjustment, whereas item nonresponses are handled by some form of imputation. This paper reviews methods of weighting adjustment and imputation and discusses their properties.

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In this paper, different types of response/nonresponse and associated measures such as rates are provided and discussed together with their implications on both estimation and administrative procedures. The missing data problems lead to inconsistent terminology related to nonresponse such as completion rates, eligibility rates, contact rates, and refusal rates, many of which can be defined in different ways. In addition, there are item nonresponse rates as well as characteristic response rates. Depending on the uses, the rates may be weighted or unweighted.

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Using the optimal estimating functions for survey sampling estimation (Godambe and Thompson 1986), we obtain some optimality results for nonresponse situations in survey sampling.

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Multiple imputation is a technique for handling survey nonresponse that replaces each missing value created by nonresponse by a vector of possible values that reflect uncertainty about which values to impute. A simple example and brief overview of the underlying theory are used to introduce the general procedure.

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Statistics Canada has undertaken a project to develop a generalized edit and imputation system, the intent of which is to meet the processing requirements of most of its surveys. The various approaches to imputation for item non-response, which have been proposed, will be discussed. Important issues related to the implementation of these proposals into a generalized setting will also be addressed.

Description: This product is the dictionary for the Longitudinal Administrative Databank (LAD). The dictionary contains a complete description for each of the income and demographic variables in the LAD, including name, acronym, definition, source, historical availability and historical continuity.

The following is a partial list of LAD variables: age, sex, marital status, family type, number and age of children, total income, wages and salaries, self-employment, Employment Insurance, Old Age Security, Canada and Quebec Pension Plans, social assistance, investment income, rental income, alimony, registered retirement savings plan (RRSP) income and contributions, low-income status, full-time education deduction, provincial refundable tax credits, goods and service tax (GST) credits, Canada Child Tax Benefits, selected immigration variables, Tax Free Savings (TFSA) information and Canadian Controlled Private Corporations (CCPC) information.

Description: The Coverage Technical Report will present the errors included in census data that result from persons who are either missed (not enumerated) or enumerated more than once. The population coverage error is one of the most important types of errors because it affects the accuracy of not only population counts, but also all the census data results that describe the characteristics of the population universe.

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: This product contains gridded datasets of annual and 30-year average estimates of water yield. Tracking water yield—an estimate of renewable water supply derived from National Water Data Archive (HYDAT) streamflow data—provides information to help understand water resources available for human use and ecosystem needs. Annual datasets are available for the years 1971 to 2021 and cover southern Canada. Thirty-year averages are available for 1971-2000, 1981-2010, and 1991-2020. They cover the terrestrial and freshwater extent of Canada, except for the Arctic Archipelago.

Description: This product contains specifications intended for users of the water yield geospatial files. This document provides important technical information for users and links to methodology.

Description: Spatial information products provide users with data for visualization, reference, mapping and spatial analysis using geographical information systems (GIS). Available files include spatial environmental data as well as documentation and metadata. This information is released as part of a suite of products associated with the Census of Environment (CoE). The CoE organizes data about Canada’s natural environment using the System of Environmental-Economic Accounting – Ecosystem Accounting international statistical standard, which takes a spatial approach to accounting for Canada’s ecosystems and natural capital.

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: This guide is intended to provide a detailed review of both the 2022 IPS and IPS–NIS with respect to subject matter and methodological approaches. It is designed to help data users by serving as a guide to the concepts and measures of the survey as well as the technical details of the survey’s design, field work and data processing. This guide is meant to provide users with helpful information on how to use and interpret survey results. The discussion on data quality also allows users to review the strengths and limitations of the data for their particular needs.

Chapter 1 of this guide provides an overview of the 2022 IPS and IPS–NIS by introducing the survey background and objectives. Chapter 2 outlines the survey’s themes and explains the key concepts and definitions used for the survey. Chapters 3 to 6 cover important aspects of the survey methodology, sampling design, data collection and processing. Chapters 7 and 8 review issues of data quality and caution users about comparing 2022 IPS or IPS–NIS data with data from other sources. Chapter 9 outlines the survey products available to the public, including data tables, analytical articles and reference material. The appendices provide a comprehensive list of survey indicators, extra coding categories and standard classifications used on both the IPS and the IPS–NIS. Lastly, a glossary of survey terms and information on confidence intervals is also provided.

Description: The Guide to Employment Insurance Statistics (EIS) summarizes the survey methodology and data source and includes a dictionary of concepts and definitions used by the program.

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.