Analysis

Description:

This study purports to assess whether there are temporal relationships between Unemployment Insurance Beneficiaries, Total Unemployment, Job Losers and Job Leavers in Canada using univariate and multivariate time series methods. The results indicate that during 1975-82 the Unemployment Insurance Beneficiaries series leads: (1) Total Unemployment by one month and (2) Job Leavers by two months. On the other hand, there are evidence of a feedback relationship between Unemployment Insurance Beneficiaries and Job Losers.

Description:

Thirty basic principles of questionnaire design are presented covering the content, wording, format, and testing of questionnaires. The extent to which the questionnaire is an integral part of the survey is emphasized as is consideration of its relationship with other aspects of survey design.

Description:

Twelve administrative data files are reviewed to determine if some of them could be used to derive migration data, in case the universality of the currently used family allowance files be limited, as a result of federal legislation.

It is found that none of the twelve files have strengths and weaknesses strictly comparable to those of the family allowance files. Further developments of the Health Care, and to a lesser extent the Old Age Security files are highly recommended.

Description:

In Canada, provincial and federal demographers have attempted to use various sets of administrative data to estimate migration flows. This paper presents the development of intra-provincial migration estimates using driver’s licence data in Ontario. An evaluation of these migration estimates has been carried out by comparing with those derived from the income tax data by Statistics Canada. Both files provide equally good and complimentary estimates of intra-provincial migration.

Description:

This paper examines the use of administrative files from Alberta’s Health Care Insurance Plans combined with Vital Statistics data as inputs for estimating population. Results, which are presented and compared with Census data, indicate that Health Care data can be used to produce accurate population estimates at the provincial level and for smaller areas such as census divisions and municipalities.

Description:

The accuracy of small area population estimates derived from a regression based model is heavily dependent on the ability of the indicator data selected to accurately reflect population change. Hence, prior knowledge as to the characteristics of the administrative data used as potential population indicators in a regression model is important. This report summarizes the strengths and weaknesses associated with the use of residential hydro accounts in the British Columbia regression based population estimation model.

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This paper describes a method of producing current age/sex specific population estimates for small areas utilizing as inputs total population estimates, birth and death data and estimates of historical residual net migration. An evaluation based on the 1981 Census counts for census divisions and school districts in British Columbia is presented.

Description:

A methodology has been developed for producing population estimates by single years of age and sex for small areas (census divisions and census metropolitan areas). To assure reliability, the estimates by single years of age are grouped into five years and only these grouped data are recomended for dissemination. They are based on the age-sex composition of population from the last census, births by sex, deaths by single years of age and sex, estimates of migration by age and sex, and counts of family allowance recipients in the age group 1-14 years.

Description:

Statistics Canada’s current methodologies forestimating the population of census divisions and census metropolitan areas are the regression-nested and component methods. This paper presents the experience with these estimates for the period 1981 to 1985, focusing on problems encountered with the input data on family allowance recipients.

Description:

There are many people called statisticians who carry out a very diverse set of activities which are labelled statistics. As part of the invited address at the 1985 meeting of the Statistical Society of Canada, the author presents his views and discusses the nature of the relationships between the different types of statisticians.

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

Description: This short video explains how it can be very effective for all levels of governments and organizations that serve communities to use disaggregated data to make evidence-informed public policy decisions. By using disaggregated data, policymakers are able to design more appropriate and effective policies that meet the needs of each diverse and unique Canadian.

Description: This short video explains how the use of disaggregated data can help policymakers to develop more targeted and effective policies by identifying the unique needs and challenges faced by different demographic groups.

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

Description: This product presents data on the Sustainable Development Goals. They present an overview of the 17 Goals through infographics by leveraging data currently available to report on Canada’s progress towards the 2030 Agenda for Sustainable Development.

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

Description: This course is intended for Government of Canada employees who would like to learn about evaluating the quality of data for a particular use. Whether you are a new employee interested in learning the basics, or an experienced subject matter expert looking to refresh your skills, this course is here to help.

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

Description:

Gathering, exploring, analyzing and interpreting data are essential steps in producing information that benefits society, the economy and the environment. In this video, we will discuss the importance of considering data ethics throughout the process of producing statistical information.

As a pre-requisite to this video, make sure to watch the video titled “Data Ethics: An introduction” also available in Statistics Canada’s data literacy training catalogue.

Description:

In this video, you will learn the answers to the following questions: What are the different types of error? What are the types of error that lead to statistical bias? Where during the data journey statistical bias can occur?

Description: This article provides information about population totals in the Labour Force Survey (LFS), including details on who is included in the survey target population, and a description of the methodology used to produce monthly population totals in the LFS. The note also provides guidance on how to interpret population statistics in the LFS, and discusses the extent to which the LFS can be used to examine disaggregated labour market indicators for new immigrants and non-permanent residents.

Description: This document briefly describes the small area estimation methodology developed to produce monthly estimates of employment and unemployment rate for census metropolitan areas, census agglomerations, and self-contained labour areas using data from the Labour Force Survey, Employment Insurance statistics and population projections.

Description: This study uses data from multiple waves of the Canadian Social Survey (CSS) to examine trends in three key Quality of Life indicators, namely life satisfaction, experiences of financial hardship, and future outlook. Monitoring these well-being indicators following periods of considerable social and economic change is particularly important. Beginning in the summer of 2021, the CSS, a new quarterly survey, captured the latter part of the COVID-19 pandemic as well as the rising cost of living in Canada, allowing for an understanding of how Canadians are coping with these challenges.

Description: In this paper, we look for presence of heterogeneity in conducting impact evaluations of the Skills Development intervention delivered under the Labour Market Development Agreements. We use linked longitudinal administrative data covering a sample of Skills Development participants from 2010 to 2017. We apply a causal machine-learning estimator as in Lechner (2019) to estimate the individualized program impacts at the finest aggregation level. These granular impacts reveal the distribution of net impacts facilitating further investigation as to what works for whom. The findings suggest statistically significant improvements in labour market outcomes for participants overall and for subgroups of policy interest.

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:

Statistics Canada is engaged in the "Information System for Science and Technology Project" to develop useful indicators of activity and a framework to tie them together into a coherent picture of science and technology (S&T) in Canada. The working papers series is used to publish results of the different initiatives conducted within this project. The data are related to the activities, linkages and outcomes of S&T. Several key areas are covered such as: innovation, technology diffusion, human resources in S&T and interrelations between different actors involved in S&T. This series also presents data tabulations taken from regular surveys on research and development (R&D) and S&T and made possible by the project.

Description:

This publication shows readers how to design and conduct a census or sample survey. It explains basic survey concepts and provides information on how to create efficient and high quality surveys. It is aimed at those involved in planning, conducting or managing a survey and at students of survey design courses.

This book contains the following information:

-how to plan and manage a survey;-how to formulate the survey objectives and design a questionnaire; -things to consider when determining a sample design (choosing between a sample or a census, defining the survey population, choosing a survey frame, identifying possible sources of survey error); -choosing a method of collection (self-enumeration, personal interviews or telephone interviews; computer-assisted versus paper-based questionnaires); -organizing and conducting data collection operations;-determining the sample size, allocating the sample across strata and selecting the sample; -methods of point estimation and variance estimation, and data analysis; -the use of administrative data, particularly during the design and estimation phases-how to process the data (which consists of all data handling activities between collection and estimation) and use quality control and quality assurance measures to minimize and control errors during various survey steps; and-disclosure control and data dissemination.

This publication also includes a case study that illustrates the steps in developing a household survey, using the methods and principles presented in the book. This publication was previously only available in print format and originally published in 2003.

Description:

Beginning in late 2006, the Social and Aboriginal Statistics Division of Statistics Canada embarked on the process of review of questions used in the Census and in surveys to produce data about Aboriginal peoples (North American Indian, Métis and Inuit). This process is essential to ensure that Aboriginal identification questions are valid measures of contemporary Aboriginal identification, in all its complexity. Questions reviewed included the following (from the Census 2B questionnaire):- the Ethnic origin / Aboriginal ancestry question;- the Aboriginal identity question;- the Treaty / Registered Indian question; and- the Indian band / First Nation Membership question.

Additional testing was conducted on Census questions with potential Aboriginal response options: the population group question (also known as visible minorities), and the Religion question. The review process to date has involved two major steps: regional discussions with data users and stakeholders, and qualitative testing. The regional discussions with over 350 users of Aboriginal data across Canada were held in early 2007 to examine the four questions used on the Census and other surveys of Statistics Canada. Data users included National Aboriginal organizations, Aboriginal Provincial and Territorial Organizations, Federal, Provincial and local governments, researchers and Aboriginal service organizations. User feedback showed that main areas of concern were data quality, undercoverage, the wording of questions, and the importance of comparability over time.

Description:

This report presents details on the data sources and methods underlying the air quality indicators as they were reported in Canadian Environmental Sustainability Indicators, 2007 (16-251-XWE). The air quality indicators focus on human exposure to ground-level ozone and fine particulate matter.

Details on the indicators reported after 2007 can be found on Environment Canada's site: &&www.ec.gc.ca/indicateurs-indicators/

Description:

This report presents details on the data sources and methods underlying the freshwater quality indicator as it was reported in the Canadian Environmental Sustainability Indicators, 2007 (16-251-XWE). The national freshwater quality indicator provides an overall measure of the suitability of water bodies to support aquatic life in selected monitoring sites in Canada.

Details on this indicator reported after 2007 can be found on Environment Canada's site: www.ec.gc.ca/indicateurs-indicators/

Description:

This report summarizes the main issues raised in these meetings. Four questions used to identify Aboriginal people from the Census and surveys were considered in the discussions.Statistics Canada regularly reviews the questions used on the Census and other surveys to ensure that the resulting data are representative of the population. As a first step in the process to review the questions used to produce data about First Nations, Inuit and Métis populations, regional discussions were held with more than 350 users of Aboriginal data in over 40 locations across Canada during the winter, spring and early summer of 2007.

This report summarizes the main issues raised in these meetings. Four questions used to identify Aboriginal people from the Census and surveys were considered in the discussions.

Description:

This feasibility report provides a blueprint for improving data on fraud in Canada through a survey of businesses and through amendments to the Uniform Crime Reporting (UCR) Survey. Presently, national information on fraud is based on official crime statistics reported by police services to the Uniform Crime Reporting Survey. These data, however, do not reflect the true nature and extent of fraud in Canada due to under-reporting of fraud by individuals and businesses, and due to inconsistencies in the way frauds are counted within the UCR Survey. This feasibility report concludes that a better measurement of fraud in Canada could be obtained through a survey of businesses. The report presents the information priorities of government departments, law enforcement and the private sector with respect to the issue of fraud and makes recommendations on how a survey of businesses could help fulfill these information needs.

To respond to information priorities, the study recommends surveying the following types of business establishments: banks, payment companies (i.e. credit card and debit card companies), selected retailers, property and casualty insurance carriers, health and disability insurance carriers and selected manufacturers. The report makes recommendations regarding survey methodology and questionnaire content, and provides estimates for timeframes and cost.

The report also recommends changes to the UCR Survey in order to improve the way in which incidents are counted and to render the data collected more relevant with respect to the information priorities raised by government, law enforcement and the private sector during the feasibility study.

Description:

This document summarizes the results of content analyses of the 2004 Census Test. The first section briefly explains the context of the content analyses by describing the nature of the sample, its limitations and the strategies used to evaluate data quality. The second section provides an overview of the results for questions that have not changed since the 2001 Census by describing the similarities between 2001 and 2004 distributions and non-response rates. The third section evaluates data quality of new census questions or questions that have changed substantially: same-sex married couples, ethnic origins, levels of schooling, location where highest diploma was obtained, school attendance, permission to access income tax files, and permission to make personal data publicly available 92 years after the census. The last section summarizes the overall results for questions whose content was coded and evaluated as part of the 2004 test, namely industry, occupation and place of work variables.

Description: The Economic Analysis Methodology Paper Series circulates information on definitions employed, standards used, procedures followed and evaluations of the quality of the economic statistics produced by the System of National Accounts (SNA). These papers can be downloaded free at www.statcan.gc.ca.

Description:

This report describes sampling and weighting procedures used in the 2001 Census. It reviews the history of these procedures in Canadian censuses, provides operational and theoretical justifications for them, and presents the results of the evaluation studies of these procedures.