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Description:

Aboriginal Statistics at a Glance provides data users with a thematic guide to Aboriginal data at Statistics Canada. It includes data for the First Nations (North American Indian), Métis, and Inuit populations. Each theme is illustrated with a chart presenting key indicators, a plain language definition of the indicator and links to related data tables and published articles to further assist users in meeting their data needs. Data sources include the 1996, 2001 and 2006 censuses of population, the 2006 Aboriginal Peoples Survey, the 2005 Canadian Community Health Survey, and the 2007/2008 Adult Correctional Services Survey.

Description:

Aboriginal Statistics at a Glance is a thematic guide to Aboriginal data at Statistics Canada. Each theme is illustrated with a chart presenting statistical information on a basic indicator, a plain language definition and links to related information to further assist people in meeting their data needs.

Description:

This paper investigates whether registered pension plans (RPPs) help households prepare financially for retirement or simply substitute for other forms of private saving. This issue is addressed using a panel of 1.8 million Canadian households, from 1991 to 2010, which appear in the Longitudinal Administrative Databank. The analysis controls for correlations in savings across accounts due to unobserved tastes for saving by exploiting the fact that employer contribution rates increase discontinuously on earnings above the average industrial wage, a unique feature of occupational pensions in Canada, the effect being estimated in a Regression Kink Design.

Description:

This fact sheet looks at the environmental quality of surface water sources prior to treatment using data from the 2013 Survey of Drinking Water Plants.

Description:

Self-weighting estimation through equal probability selection methods (epsem) is desirable for variance efficiency. Traditionally, the epsem property for (one phase) two stage designs for estimating population-level parameters is realized by using each primary sampling unit (PSU) population count as the measure of size for PSU selection along with equal sample size allocation per PSU under simple random sampling (SRS) of elementary units. However, when self-weighting estimates are desired for parameters corresponding to multiple domains under a pre-specified sample allocation to domains, Folsom, Potter and Williams (1987) showed that a composite measure of size can be used to select PSUs to obtain epsem designs when besides domain-level PSU counts (i.e., distribution of domain population over PSUs), frame-level domain identifiers for elementary units are also assumed to be available. The term depsem-A will be used to denote such (one phase) two stage designs to obtain domain-level epsem estimation. Folsom et al. also considered two phase two stage designs when domain-level PSU counts are unknown, but whole PSU counts are known. For these designs (to be termed depsem-B) with PSUs selected proportional to the usual size measure (i.e., the total PSU count) at the first stage, all elementary units within each selected PSU are first screened for classification into domains in the first phase of data collection before SRS selection at the second stage. Domain-stratified samples are then selected within PSUs with suitably chosen domain sampling rates such that the desired domain sample sizes are achieved and the resulting design is self-weighting. In this paper, we first present a simple justification of composite measures of size for the depsem-A design and of the domain sampling rates for the depsem-B design. Then, for depsem-A and -B designs, we propose generalizations, first to cases where frame-level domain identifiers for elementary units are not available and domain-level PSU counts are only approximately known from alternative sources, and second to cases where PSU size measures are pre-specified based on other practical and desirable considerations of over- and under-sampling of certain domains. We also present a further generalization in the presence of subsampling of elementary units and nonresponse within selected PSUs at the first phase before selecting phase two elementary units from domains within each selected PSU. This final generalization of depsem-B is illustrated for an area sample of housing units.

Description:

This paper develops allocation methods for stratified sample surveys where composite small area estimators are a priority, and areas are used as strata. Longford (2006) proposed an objective criterion for this situation, based on a weighted combination of the mean squared errors of small area means and a grand mean. Here, we redefine this approach within a model-assisted framework, allowing regressor variables and a more natural interpretation of results using an intra-class correlation parameter. We also consider several uses of power allocation, and allow the placing of other constraints such as maximum relative root mean squared errors for stratum estimators. We find that a simple power allocation can perform very nearly as well as the optimal design even when the objective is to minimize Longford’s (2006) criterion.

Description:

Rotating panels are widely applied by national statistical institutes, for example, to produce official statistics about the labour force. Estimation procedures are generally based on traditional design-based procedures known from classical sampling theory. A major drawback of this class of estimators is that small sample sizes result in large standard errors and that they are not robust for measurement bias. Two examples showing the effects of measurement bias are rotation group bias in rotating panels, and systematic differences in the outcome of a survey due to a major redesign of the underlying process. In this paper we apply a multivariate structural time series model to the Dutch Labour Force Survey to produce model-based figures about the monthly labour force. The model reduces the standard errors of the estimates by taking advantage of sample information collected in previous periods, accounts for rotation group bias and autocorrelation induced by the rotating panel, and models discontinuities due to a survey redesign. Additionally, we discuss the use of correlated auxiliary series in the model to further improve the accuracy of the model estimates. The method is applied by Statistics Netherlands to produce accurate official monthly statistics about the labour force that are consistent over time, despite a redesign of the survey process.

Description:

We propose a model-assisted extension of weighting design-effect measures. We develop a summary-level statistic for different variables of interest, in single-stage sampling and under calibration weight adjustments. Our proposed design effect measure captures the joint effects of a non-epsem sampling design, unequal weights produced using calibration adjustments, and the strength of the association between an analysis variable and the auxiliaries used in calibration. We compare our proposed measure to existing design effect measures in simulations using variables like those collected in establishment surveys and telephone surveys of households.

Description:

Careful design of a dual-frame random digit dial (RDD) telephone survey requires selecting from among many options that have varying impacts on cost, precision, and coverage in order to obtain the best possible implementation of the study goals. One such consideration is whether to screen cell-phone households in order to interview cell-phone only (CPO) households and exclude dual-user household, or to take all interviews obtained via the cell-phone sample. We present a framework in which to consider the tradeoffs between these two options and a method to select the optimal design. We derive and discuss the optimum allocation of sample size between the two sampling frames and explore the choice of optimum p, the mixing parameter for the dual-user domain. We illustrate our methods using the National Immunization Survey, sponsored by the Centers for Disease Control and Prevention.

Description:

Félix-Medina and Thompson (2004) proposed a variant of link-tracing sampling to sample hidden and/or hard-to-detect human populations such as drug users and sex workers. In their variant, an initial sample of venues is selected and the people found in the sampled venues are asked to name other members of the population to be included in the sample. Those authors derived maximum likelihood estimators of the population size under the assumption that the probability that a person is named by another in a sampled venue (link-probability) does not depend on the named person (homogeneity assumption). In this work we extend their research to the case of heterogeneous link-probabilities and derive unconditional and conditional maximum likelihood estimators of the population size. We also propose profile likelihood and bootstrap confidence intervals for the size of the population. The results of simulations studies carried out by us show that in presence of heterogeneous link-probabilities the proposed estimators perform reasonably well provided that relatively large sampling fractions, say larger than 0.5, be used, whereas the estimators derived under the homogeneity assumption perform badly. The outcomes also show that the proposed confidence intervals are not very robust to deviations from the assumed models.

Description:

This publication provides information on average air fares by sector and fare type group and average domestic air fares for ten selected cities of enplanement. It also provides information on the distribution of passengers and passenger-kilometres by sector and fare type group. In addition to annual data, this publication also presents quarterly data. It also includes data highlights and a brief analysis.

Description:

Gross domestic expenditure on research and development (GERD) is a statistical series, constructed by adding together the intramural expenditures on R&D as reported by the performing sectors. As a term used by OECD Member countries, it is defined as total intramural expenditure on R&D performed on the national territory during a given period. GERD includes R&D performed within a country and funded from abroad but excludes payments for R&D performed abroad.

Description:

These analytical products present projections of the Canadian population by Aboriginal identity, place of residence, and other variables of interest according to various scenarios.

Description:

This report is a joint publication of Statistics Canada and Transport Canada. It is also known as Transport Canada Report TP 577. This report presents annual statistics for Canadian airports without NAV CANADA air traffic control towers and/or flight service stations.

Description:

This report is a joint publication of Statistics Canada and Transport Canada. It is also known as Transport Canada Report TP 577. This report presents annual statistics for Canadian airports with NAV CANADA air traffic control towers and/or flight service stations.

Description: This publication presents an overview of the economic developments reported in Canada's national accounts for the most recent quarter, and is no longer being released. The overview covers several broad areas: 1) gross domestic product (GDP) by income and by expenditure; 2) GDP by industry; 3) balance of international payments accounts; 4) labour productivity and other related variables; 5) international investment position; and, 6) national balance sheet accounts.

Description:

Using 2011 Census data, this profile provides a statistical overview of the age and sex variables as well as families, households, marital status, structural type of dwelling and collectives and language characteristics for Canada, provinces, territories, census divisions and census subdivisions.

In the census product line, groups of related variables are referred to as 'release components of profiles.' These are made available with the major releases of variables of the census cycle, starting with age and sex. Together, they will form a complete Census Profile of all the variables for each level of geography, plus one cumulative profile for the dissolved census subdivisions. Starting with the age and sex major day of release, and on major days of release thereafter, profile component data are available at the Canada, province and territory, economic region, census division and census subdivision levels, at the census metropolitan area, census agglomeration, population centre, and census tract levels, designated places, and at the federal electoral district (based on the 2003 Representation Order) level. Profile component data for all other standard geographic areas, including dissemination areas, dissolved census subdivisions, and forward sortation areas, will be available after the major days of release.

Description:

Using 2011 National Household Survey (NHS) data, this profile provides a statistical overview of variables describing immigration and ethnocultural diversity, Aboriginal peoples, education, labour, mobility and migration, income and earnings, and housing and shelter costs.

In the National Household Survey product line, groups of related variables are referred to as 'release components of profiles.' These are made available with the major releases of variables of the NHS cycle, starting with the Immigration and Ethnocultural Diversity, and Aboriginal Peoples releases. Together, they will form a complete NHS Profile of all the variables for each level of geography. Profile-component data are available at the Canada, province and territory, census division and census subdivision levels, at the census metropolitan area and census agglomeration levels, census tract level, and at the federal electoral district (based on the 2003 Representation Order) level.

Description:

The census is designed to provide information about the demographic and social characteristics of the people living in Canada and the housing or dwelling units they occupy.

'Language' is the final major release of data for the 2011 Census of Population. Data are presented in different analytical and data products which illustrate the linguistic composition of the Canadian population, including languages spoken at home and knowledge of English, French and non-official languages, by other demographic characteristics.

Analytical products

The analytical document provides analysis on the key findings and trends in the data, and is complemented with highlight tables which present key indicators for various levels of geography, and the short articles found in the Census in Brief and the Focus on Geography Series.

Data products

The Census Profile is one data product which provides a statistical overview of user selected geographic areas based on a number of detailed variables and/or groups of variables. Other data products include topic-based tabulations which are a series of cross-tabulations ranging in complexity and are available for various levels of geography, as well as the Visual Census which provides a visual representation of selected variables accompanied by their tabular source data.

Description:

The Industry Accounts Division of Statistics Canada publishes annual supply and use input-output (I-O) tables. While these rectangular, industry by commodity closely reflect actual economic transactions, certain analytical and modeling purposes, however, require symmetric industry-by-industry I-O tables. The symmetric industry by industry table shows the inter-industry transactions, that is, all purchases of an industry from all other industries including expenditures on imports and inventory withdrawals as well as all expenditures on primary inputs. Similarly, the symmetric final demand table shows all purchases by a final demand category from all other industries, including expenditures on imports and inventory withdrawals as well as all expenditures on indirect taxes. These tables are available at the L level. Some data suppression is necessary at the L level due to confidentiality requirements. Explanation on the methodology used is provided to the user by contacting the Industry Accounts Division of Statistics Canada.

Description:

Aboriginal Statistics at a Glance provides data users with a thematic guide to Aboriginal data at Statistics Canada. It includes data for the First Nations (North American Indian), Métis, and Inuit populations. Each theme is illustrated with a chart presenting key indicators, a plain language definition of the indicator and links to related data tables and published articles to further assist users in meeting their data needs. Data sources include the 1996, 2001 and 2006 censuses of population, the 2006 Aboriginal Peoples Survey, the 2005 Canadian Community Health Survey, and the 2007/2008 Adult Correctional Services Survey.

Description:

Aboriginal Statistics at a Glance is a thematic guide to Aboriginal data at Statistics Canada. Each theme is illustrated with a chart presenting statistical information on a basic indicator, a plain language definition and links to related information to further assist people in meeting their data needs.

Description:

This paper investigates whether registered pension plans (RPPs) help households prepare financially for retirement or simply substitute for other forms of private saving. This issue is addressed using a panel of 1.8 million Canadian households, from 1991 to 2010, which appear in the Longitudinal Administrative Databank. The analysis controls for correlations in savings across accounts due to unobserved tastes for saving by exploiting the fact that employer contribution rates increase discontinuously on earnings above the average industrial wage, a unique feature of occupational pensions in Canada, the effect being estimated in a Regression Kink Design.

Description:

This fact sheet looks at the environmental quality of surface water sources prior to treatment using data from the 2013 Survey of Drinking Water Plants.

Description:

Self-weighting estimation through equal probability selection methods (epsem) is desirable for variance efficiency. Traditionally, the epsem property for (one phase) two stage designs for estimating population-level parameters is realized by using each primary sampling unit (PSU) population count as the measure of size for PSU selection along with equal sample size allocation per PSU under simple random sampling (SRS) of elementary units. However, when self-weighting estimates are desired for parameters corresponding to multiple domains under a pre-specified sample allocation to domains, Folsom, Potter and Williams (1987) showed that a composite measure of size can be used to select PSUs to obtain epsem designs when besides domain-level PSU counts (i.e., distribution of domain population over PSUs), frame-level domain identifiers for elementary units are also assumed to be available. The term depsem-A will be used to denote such (one phase) two stage designs to obtain domain-level epsem estimation. Folsom et al. also considered two phase two stage designs when domain-level PSU counts are unknown, but whole PSU counts are known. For these designs (to be termed depsem-B) with PSUs selected proportional to the usual size measure (i.e., the total PSU count) at the first stage, all elementary units within each selected PSU are first screened for classification into domains in the first phase of data collection before SRS selection at the second stage. Domain-stratified samples are then selected within PSUs with suitably chosen domain sampling rates such that the desired domain sample sizes are achieved and the resulting design is self-weighting. In this paper, we first present a simple justification of composite measures of size for the depsem-A design and of the domain sampling rates for the depsem-B design. Then, for depsem-A and -B designs, we propose generalizations, first to cases where frame-level domain identifiers for elementary units are not available and domain-level PSU counts are only approximately known from alternative sources, and second to cases where PSU size measures are pre-specified based on other practical and desirable considerations of over- and under-sampling of certain domains. We also present a further generalization in the presence of subsampling of elementary units and nonresponse within selected PSUs at the first phase before selecting phase two elementary units from domains within each selected PSU. This final generalization of depsem-B is illustrated for an area sample of housing units.

Description:

This paper develops allocation methods for stratified sample surveys where composite small area estimators are a priority, and areas are used as strata. Longford (2006) proposed an objective criterion for this situation, based on a weighted combination of the mean squared errors of small area means and a grand mean. Here, we redefine this approach within a model-assisted framework, allowing regressor variables and a more natural interpretation of results using an intra-class correlation parameter. We also consider several uses of power allocation, and allow the placing of other constraints such as maximum relative root mean squared errors for stratum estimators. We find that a simple power allocation can perform very nearly as well as the optimal design even when the objective is to minimize Longford’s (2006) criterion.

Description:

Rotating panels are widely applied by national statistical institutes, for example, to produce official statistics about the labour force. Estimation procedures are generally based on traditional design-based procedures known from classical sampling theory. A major drawback of this class of estimators is that small sample sizes result in large standard errors and that they are not robust for measurement bias. Two examples showing the effects of measurement bias are rotation group bias in rotating panels, and systematic differences in the outcome of a survey due to a major redesign of the underlying process. In this paper we apply a multivariate structural time series model to the Dutch Labour Force Survey to produce model-based figures about the monthly labour force. The model reduces the standard errors of the estimates by taking advantage of sample information collected in previous periods, accounts for rotation group bias and autocorrelation induced by the rotating panel, and models discontinuities due to a survey redesign. Additionally, we discuss the use of correlated auxiliary series in the model to further improve the accuracy of the model estimates. The method is applied by Statistics Netherlands to produce accurate official monthly statistics about the labour force that are consistent over time, despite a redesign of the survey process.

Description:

We propose a model-assisted extension of weighting design-effect measures. We develop a summary-level statistic for different variables of interest, in single-stage sampling and under calibration weight adjustments. Our proposed design effect measure captures the joint effects of a non-epsem sampling design, unequal weights produced using calibration adjustments, and the strength of the association between an analysis variable and the auxiliaries used in calibration. We compare our proposed measure to existing design effect measures in simulations using variables like those collected in establishment surveys and telephone surveys of households.

Description:

Careful design of a dual-frame random digit dial (RDD) telephone survey requires selecting from among many options that have varying impacts on cost, precision, and coverage in order to obtain the best possible implementation of the study goals. One such consideration is whether to screen cell-phone households in order to interview cell-phone only (CPO) households and exclude dual-user household, or to take all interviews obtained via the cell-phone sample. We present a framework in which to consider the tradeoffs between these two options and a method to select the optimal design. We derive and discuss the optimum allocation of sample size between the two sampling frames and explore the choice of optimum p, the mixing parameter for the dual-user domain. We illustrate our methods using the National Immunization Survey, sponsored by the Centers for Disease Control and Prevention.

Description:

Félix-Medina and Thompson (2004) proposed a variant of link-tracing sampling to sample hidden and/or hard-to-detect human populations such as drug users and sex workers. In their variant, an initial sample of venues is selected and the people found in the sampled venues are asked to name other members of the population to be included in the sample. Those authors derived maximum likelihood estimators of the population size under the assumption that the probability that a person is named by another in a sampled venue (link-probability) does not depend on the named person (homogeneity assumption). In this work we extend their research to the case of heterogeneous link-probabilities and derive unconditional and conditional maximum likelihood estimators of the population size. We also propose profile likelihood and bootstrap confidence intervals for the size of the population. The results of simulations studies carried out by us show that in presence of heterogeneous link-probabilities the proposed estimators perform reasonably well provided that relatively large sampling fractions, say larger than 0.5, be used, whereas the estimators derived under the homogeneity assumption perform badly. The outcomes also show that the proposed confidence intervals are not very robust to deviations from the assumed models.

Description: This report describes sampling and weighting procedures used in the 2011 National Household Survey. It provides operational and theoretical justifications for them, and presents the results of the evaluation studies of these procedures.

Description:

This paper introduces and explains modifications made to the Labour Force Survey estimates in January 2015. Some of these modifications include the adjustment of all LFS estimates to reflect population counts based on the 2011 Census and includes updates to 2011 Geography classification system.

Description:

This report describes the quality indicators produced for the 2013 Survey of Household Spending. These quality indicators, such as coefficients of variation, nonresponse rates, slippage rates and imputation rates, help users interpret the survey data.