Analysis

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: 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.

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An examination of trends in unemployment rate data as far back as 1921.

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Self-employment is an increasingly popular form of non-standard work.

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How does the Work Sharing Program prevent layoffs?

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In 1989, the Survey of Literacy Skills Used in Daily Activities was conducted to assess the reading and numerous skills of Canada's adult population. This article reports the survey's main findings.

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This paper presents results of an empirical study on fitting log-linear models to data on estimates of characteristics and their coefficients of variation (CV) from the Canadian Labour Force Survey. The characteristics were classified into groups on the basis of design effects and models were fitted to data on estimates of characteristic totals and their CVs over twelve month period. The models can be used in situations where estimates of CV are needed for new characteristics, and for providing more precise estimates of reliability of estimates based on past data. The problem of evaluation of fit of the models is considered.

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The methodology of the For-hire Trucking Survey is discussed in this paper. This survey provides good examples of administrative and operational constraints faced by survey statisticians and field data collection teams.

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An aspect of surveys not always given adequate consideration is maintenance.

The scope and importance of survey maintenance are discussed and a case is made for a more scientific methodological approach. Practical applications to various stages of surveys are illustrated by examples from the Canadian Labour Force Survey.

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In surveys a response may be incomplete or some items may be inconsistent or, as in the case of two-phase sampling, items may be unavailable. In these cases it may be expedient to impute values for the missing items. While imputation is not a particularly good solution to any specific estimation problem, it does permit the production of arbitrary estimates in a consistent way.

The survey statistician may have to cope with a mixture of numerical and categorical items, subject to a variety of constraints. He should evaluate his technique, especially with respect to bias. He should make sure that imputed items are clearly identified and summary reports produced.

A variety of imputation techniques in current use is described and discussed, with particular reference to the practical problems involved.

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A FORTRAN Subroutine to obtain the “working probabilities” for Fellegi’s (1963) method of unequal probability sampling is given. The solution is obtained by an iterative procedure where the starting values for the (k+l)th draw “working probabilities” are the solutions for the kth draw “working probabilities” and the iterative procedure is terminated when a prespecified accuracy is achieved. The limitation is that the Subroutine can only be used to obtain up to and including the 5th draw “working probabilities”. It was observed that the convergence occurs very fast in double precision. Therefore all real variables have been declared as double precision. The joint selection probabilities \Pi_{ij}’s i.e. the probability that both the ith and jth units are in the sample are obtained by summing the probabilities of selecting those samples that contain both the ith and jth units. The joint selection probabilities are required for the variance estimation of the Horvitz-Thompson estimator of population total of the characteristic of interest.

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Survey organizations undertake periodic redesigns of continuous surveys. Reasons for such redesigns related to changes in information needs to be satisfied by the survey and changes in public awareness and attitudes towards surveys are discussed in the context of the redesign of the Canadian Labour Force Survey following the 1981 Census. In particular, the importance of close dialogue between users of the survey data and design statisticians at the early stages of the redesign process in order to establish survey objectives is stressed.

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The Department of Supply and Services’ role and procedures are outlined as they relate to those using the services of the Department of Supply and Services and those receiving contracts.

There are two basic principles which cover all the policies and procedures. These are: i) the equality of opportunity to compete for Government contracts must be afforded to all qualified suppliers; and ii) that fair value for the taxpayers’ dollar must be obtained.

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This paper discusses some of the changes in market research we should expect in the next decade. Currently, studies are issue oriented: they provide answers to specific questions or marketing issues. The next decade will see research projects with a broader scope: to understand how markets work and why consumers behave as they do. Measurements will be more complex, and multivariate analysis techniques will be used extensively to identify the subtle relationships within the data. Marketing models will be the conceptual framework for these more complex studies. Market analysis identifying consumer responsiveness segments provides a case example of what might be expected from model-based market research studies.

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This paper identifies the stages in the life-cycle of government policies and programs. For each stage, examples are given of how survey research is presently used and likely trends over the next decade are identified.

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This document describes the process of commissioning market research at Imperial Oil Limited. It outlines the management processes that precede commissioning and defines the expectations of a typical buyer of research work. It also examines the need to have a satisfactory business relationship between the buyer and the seller, and it provides a list of the attributes most often considered by a company seeking a supplier for a particular research project.

Description: Environment fact sheets will include short, focused, single-theme analysis on key issues within the changing environment with regards to all Canadians. Over the course of the series, analysis will include topics on: air and climate, pollution and waste, environmental protection and quality, and natural resources.

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Description: This publication presents key highlights and results from the General Social Survey on the topics of caregiving and care receiving; social identity; giving, volunteering and participating; victimization; time use; and family.

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Description: The Canadian Survey on Disability (CSD) is a national survey of Canadians aged 15 and over whose everyday activities are limited because of a long-term condition or health-related problem.

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Description: This publication brings together and analyzes a wide range of data sources in order to provide information on various aspects of Canadian society, including labour, income, education, social, and demographic issues, that affect the lives of Canadians.

Description: This publication presents annual estimates of population for subprovincial areas of Canada, such as census metropolitan areas (CMAs), census agglomerations (CAs), economic regions (ERs) and census divisions (CDs). The following components of population change are also presented: births, deaths, immigration, emigration, returning emigration, net temporary emigration, net non-permanent residents and interprovincial and intraprovincial migration. The estimates are based on the most recent census of population results available at the time of publication, which have been adjusted for census net undercoverage (including adjustment for incompletely enumerated Indian reserves). This publication also contains highlights and an analysis of the most recent demographic trends, as well as a description of the concepts, methods and data quality of the estimates.

Description: Reports on Special Business Projects is an occasional series that focuses primarily on the results of special surveys or special projects conducted by the Centre for Special Business Projects. The reports cover a wide range of topics, which include business performance and trends, custom tabulations of business data, economic impact studies, new measurement frameworks and indicators to support program development, monitoring and performance assessment, territorial economic indicators and other special studies.

Description: Short and focused data tables related to current events.