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Description: Number of employment insurance claims received by province and territory, last 5 months.

Description: Number of employment insurance claims received and allowed, by province and territory and type of claim, last 5 months.

Description: Number of persons covered by employment insurance, last 5 months.

Description: Benefit payments and number of benefit weeks of employment insurance benefits, by class of worker and type of income benefits, last 5 months.

Description: Benefit payments and number of benefit weeks of employment insurance regular income benefits, last 5 months.

Description: Number of employment insurance beneficiaries by type of income benefits, age group and sex, last 5 months.

Description: Number of employment insurance beneficiaries by detailed age group, total and regular income benefits, declared earnings, and sex, last 5 months.

Description: Number of employment insurance beneficiaries receiving regular income benefits by province and territory, declared earnings, sex, and age group, last 5 months.

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Number of employment insurance beneficiaries by census division, total and regular income benefits, declared earnings, sex, and age group, last 5 months.

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Number of employment insurance beneficiaries by economic region, total and regular income benefits, declared earnings, sex, and age group, last 5 months.

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This table details private households by 1990 household income groups.

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This table details population 15 years and over by age groups and marital status, showing labour force activity and sex.

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This table details population 15 years and over by age groups and sex, showing work activity in 1990, for canada, provinces, territories, census divisions and census subdivisions, 1991.

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This table details population 15 years and over by age groups and sex, showing work activity in 1990, for canada, provinces, territories, federal electoral districts and enumeration areas, 1991 census.

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This table details population 15 years and over by age groups and sex, showing work activity in 1990, for census metropolitan areas, tracted census agglomerations and census tracts, 1991 census.

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This table details population 15 years and over by age groups and school attendance, showing labour force activity and sex.

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This table details population 15 years and over by age groups and highest level of schooling, showing labour force activity and sex.

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This table details females 15 years and over in private households by age groups, marital status and presence of children, showing labour force activity.

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This table details experienced labour force 15 years and over by sex and occupation major groups, showing age groups.

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This table details experienced labour force 15 years and over by sex and occupation major groups, showing industry divisions.

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: The Standard Classification of Countries and Areas of Interest (SCCAI) has been developed to increase coherence of the list of countries used within Statistics Canada and includes countries and areas for which statistical data are compiled. The Variant of the SCCAI for Social Statistics and the Variant of the SCCAI for Travel Statistics were developed to create groupings of countries to enable the production of integrated statistics when publishing social statistics data and travel statistics data, respectively. These variants have three levels.

Description: The Consolidated Energy Statistics table (CEST) provides national level monthly estimates of supply and demand characteristics, for both primary and secondary energy sources by fuel type. The data is presented in terajoules; a common unit of measure, allowing easy comparisons between different fuel and energy types. The table is updated with new data on a monthly basis.

Description: The Canadian Export Classification is a structured, hierarchical classification system based on the Harmonized Description and Coding System. The HS nomenclature is divided into 21 Sections, which in general, group goods produced in the same sector of the economy.

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. The 2022 CSD Concepts and Methods Guide is designed to assist CSD data users by providing relevant information on survey content and concepts, sampling design, collection methods, data processing, data quality and product availability.

Description: This product presents the Public Sector Universe, defined by Statistics Canada as a list of institutional units that are included in the economic measurement of governments in Canada. An institutional unit is defined as an economic entity that is capable, in its own right, of owning assets, incurring liabilities, and engaging in economic activities and in transactions with other entities. It includes the sectors of education, health, general government and government business enterprise sectors for all levels of government in Canada, annually, since 2008.

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 Canadian Index of Multiple Deprivation (CIMD) is an area-based index which uses Census of Population microdata to measure four key dimensions of deprivation at the dissemination area (DA)-level: residential instability, economic dependency, situational vulnerability and ethno-cultural composition.

The CIMD allows for an understanding of inequalities in various measures of health and social well-being. While it is a geographically-based index of deprivation and marginalization, it can also be used as a proxy for an individual. The CIMD has the potential to be widely used by researchers on a variety of topics related to socio-economic research. Other uses for the index may include: policy planning and evaluation, or resource allocation.

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The Canadian Index of Multiple Deprivation (CIMD) is an area-based index which uses Census of Population microdata to measure four key dimensions of deprivation at the dissemination area (DA)-level: residential instability, economic dependency, situational vulnerability and ethno-cultural composition. The CIMD allows for an understanding of inequalities in various measures of health and social well-being. While it is a geographically-based index of deprivation and marginalization, it can also be used as a proxy for an individual. The CIMD has the potential to be widely used by researchers on a variety of topics related to socio-economic research. Other uses for the index may include: policy planning and evaluation, or resource allocation.

Description: Departmental Results Reports (DRRs) are part of the Estimates family of documents. Estimates documents support appropriation acts, which specify the amounts and broad purposes for which funds can be spent by the government. The Estimates document family has three parts.

Part I (Government Expenditure Plan) provides an overview of federal spending.

Part II (Main Estimates) lists the financial resources required by individual departments, agencies and Crown corporations for the upcoming fiscal year.

Part III (Departmental Expenditure Plans) consists of two documents. Departmental Plans (DPs) are expenditure plans for each appropriated department and agency (excluding Crown corporations).

Description: The Fees Report must be tabled in parliament annually, as per the Service Fees Act, which came into force in June 2017. The Service Fees Act introduces a modern legislative framework that enables cost-effective delivery of services and, through enhanced reporting to Parliament, improved transparency and oversight.