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  • Notices and consultations: 11-628-X
    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).

    Release date: 2023-11-09

  • Articles and reports: 91F0015M2022001
    Description:

    This study proposes an estimate of the number of Canadian citizens residing abroad (Canadian diaspora).

    Release date: 2022-04-13

  • Articles and reports: 12-001-X201800254958
    Description:

    Domains (or subpopulations) with small sample sizes are called small areas. Traditional direct estimators for small areas do not provide adequate precision because the area-specific sample sizes are small. On the other hand, demand for reliable small area statistics has greatly increased. Model-based indirect estimators of small area means or totals are currently used to address difficulties with direct estimation. These estimators are based on linking models that borrow information across areas to increase the efficiency. In particular, empirical best (EB) estimators under area level and unit level linear regression models with random small area effects have received a lot of attention in the literature. Model mean squared error (MSE) of EB estimators is often used to measure the variability of the estimators. Linearization-based estimators of model MSE as well as jackknife and bootstrap estimators are widely used. On the other hand, National Statistical Agencies are often interested in estimating the design MSE of EB estimators in line with traditional design MSE estimators associated with direct estimators for large areas with adequate sample sizes. Estimators of design MSE of EB estimators can be obtained for area level models but they tend to be unstable when the area sample size is small. Composite MSE estimators are proposed in this paper and they are obtained by taking a weighted sum of the design MSE estimator and the model MSE estimator. Properties of the MSE estimators under the area level model are studied in terms of design bias, relative root mean squared error and coverage rate of confidence intervals. The case of a unit level model is also examined under simple random sampling within each area. Results of a simulation study show that the proposed composite MSE estimators provide a good compromise in estimating the design MSE.

    Release date: 2018-12-20

  • Articles and reports: 21-004-X201800100001
    Description:

    The Field Crop Reporting Series provides estimates on seeded and harvested areas, yield and production. This is a series of five data collection activities where three occasions provide preliminary data for seeded areas (March) or production (July and September), and November provides final area and production estimates. This article examines the differences between the preliminary and final estimates for field crop statistics. The field crops included in this study are canola, all wheat, soybeans, barley, oats and corn for grain. The data from 2008-2018 are used for seeded area estimates while production estimates cover 2008-2017.

    Release date: 2018-11-08

  • Articles and reports: 11-626-X2017077
    Description:

    On April 13, 2017, the Government of Canada tabled legislation to legalize the recreational use of cannabis by adults. This will directly impact Canada’s statistical system. The focus of this Economic Insights article is to provide experimental estimates for the volume of cannabis consumption, based on existing information on the prevalence of cannabis use. The article presents experimental estimates of the number of tonnes of cannabis consumed by age group for the period from 1960 to 2015. The experimental estimates rely on survey data from multiple sources, statistical techniques to link the sources over time, and assumptions about consumption behaviour. They are subject to revision as improved or additional data sources become available.

    Release date: 2017-12-18

  • Articles and reports: 11-621-M2016101
    Description:

    Using data from the Monthly Retail Trade survey, this article discusses the measurement of online retail sales in the retail trade sector.

    Release date: 2016-11-14

  • Surveys and statistical programs – Documentation: 13-606-G201600114620
    Description:

    An explanation of the structure and concepts of Canada’s income and expenditure accounts.

    Release date: 2016-08-31

  • Public use microdata: 12M0026X
    Description:

    This package was designed to help users access and manipulate the public use microdata file (PUMF – provincial) for the 2014 General Social Survey (GSS) on Canadians’ Safety (Victimization). It contains the PUMF data and describes the objectives, methodology and estimation procedures for this survey as well as guidelines for releasing estimates.

    Statistics Canada collected data on the topic of Canadians’ safety (Victimization) for the sixth time in 2014. Data were previously collected in 1988 (Cycle 3), 1993 (Cycle 8), 1999 (Cycle 13), 2004 (Cycle 18) and 2009 (Cycle 23). The 2014 provincial GSS collected data from persons aged 15 years and over living in private households in Canada, excluding residents of the Yukon, Northwest Territories and Nunavut and full time residents of institutions.

    Between 2009 and 2014, the core content of the survey was revised in a number of ways, based on experience gained from earlier iterations. Some questions were revised to improve their clarity for respondents, and others were added or dropped following consultations with stakeholders from the justice sector, government and academic communities.

    Release date: 2016-07-27

  • Articles and reports: 12-001-X201600114544
    Description:

    In the Netherlands, statistical information about income and wealth is based on two large scale household panels that are completely derived from administrative data. A problem with using households as sampling units in the sample design of panels is the instability of these units over time. Changes in the household composition affect the inclusion probabilities required for design-based and model-assisted inference procedures. Such problems are circumvented in the two aforementioned household panels by sampling persons, who are followed over time. At each period the household members of these sampled persons are included in the sample. This is equivalent to sampling with probabilities proportional to household size where households can be selected more than once but with a maximum equal to the number of household members. In this paper properties of this sample design are described and contrasted with the Generalized Weight Share method for indirect sampling (Lavallée 1995, 2007). Methods are illustrated with an application to the Dutch Regional Income Survey.

    Release date: 2016-06-22

  • Articles and reports: 12-001-X201600114545
    Description:

    The estimation of quantiles is an important topic not only in the regression framework, but also in sampling theory. A natural alternative or addition to quantiles are expectiles. Expectiles as a generalization of the mean have become popular during the last years as they not only give a more detailed picture of the data than the ordinary mean, but also can serve as a basis to calculate quantiles by using their close relationship. We show, how to estimate expectiles under sampling with unequal probabilities and how expectiles can be used to estimate the distribution function. The resulting fitted distribution function estimator can be inverted leading to quantile estimates. We run a simulation study to investigate and compare the efficiency of the expectile based estimator.

    Release date: 2016-06-22
Data (2)

Data (2) ((2 results))

  • Public use microdata: 12M0026X
    Description:

    This package was designed to help users access and manipulate the public use microdata file (PUMF – provincial) for the 2014 General Social Survey (GSS) on Canadians’ Safety (Victimization). It contains the PUMF data and describes the objectives, methodology and estimation procedures for this survey as well as guidelines for releasing estimates.

    Statistics Canada collected data on the topic of Canadians’ safety (Victimization) for the sixth time in 2014. Data were previously collected in 1988 (Cycle 3), 1993 (Cycle 8), 1999 (Cycle 13), 2004 (Cycle 18) and 2009 (Cycle 23). The 2014 provincial GSS collected data from persons aged 15 years and over living in private households in Canada, excluding residents of the Yukon, Northwest Territories and Nunavut and full time residents of institutions.

    Between 2009 and 2014, the core content of the survey was revised in a number of ways, based on experience gained from earlier iterations. Some questions were revised to improve their clarity for respondents, and others were added or dropped following consultations with stakeholders from the justice sector, government and academic communities.

    Release date: 2016-07-27

  • Table: 82F0008X
    Description:

    The special ten year anniversary edition of Canadian cancer statistics 1997 represents a collaborative effort between Statistics Canada, the National Cancer Institute of Canada, Health Canada, the Canadian Cancer Society, and provincial/territorial cancer registries. This 71 page monograph contains estimates of cancer incidence and mortality for 1997, historical (actual and estimated) data from 1969 to 1997, and selected indicators on the burden of cancer. Estimates were produced by modelling actual cancer incidence and mortality data by province for selected cancer sites. The special topic this year is a comparison of the burden of cancer in Canada in 1997 to that reported in the first edition in 1987.

    Release date: 1997-03-06
Analysis (42)

Analysis (42) (0 to 10 of 42 results)

  • Articles and reports: 91F0015M2022001
    Description:

    This study proposes an estimate of the number of Canadian citizens residing abroad (Canadian diaspora).

    Release date: 2022-04-13

  • Articles and reports: 12-001-X201800254958
    Description:

    Domains (or subpopulations) with small sample sizes are called small areas. Traditional direct estimators for small areas do not provide adequate precision because the area-specific sample sizes are small. On the other hand, demand for reliable small area statistics has greatly increased. Model-based indirect estimators of small area means or totals are currently used to address difficulties with direct estimation. These estimators are based on linking models that borrow information across areas to increase the efficiency. In particular, empirical best (EB) estimators under area level and unit level linear regression models with random small area effects have received a lot of attention in the literature. Model mean squared error (MSE) of EB estimators is often used to measure the variability of the estimators. Linearization-based estimators of model MSE as well as jackknife and bootstrap estimators are widely used. On the other hand, National Statistical Agencies are often interested in estimating the design MSE of EB estimators in line with traditional design MSE estimators associated with direct estimators for large areas with adequate sample sizes. Estimators of design MSE of EB estimators can be obtained for area level models but they tend to be unstable when the area sample size is small. Composite MSE estimators are proposed in this paper and they are obtained by taking a weighted sum of the design MSE estimator and the model MSE estimator. Properties of the MSE estimators under the area level model are studied in terms of design bias, relative root mean squared error and coverage rate of confidence intervals. The case of a unit level model is also examined under simple random sampling within each area. Results of a simulation study show that the proposed composite MSE estimators provide a good compromise in estimating the design MSE.

    Release date: 2018-12-20

  • Articles and reports: 21-004-X201800100001
    Description:

    The Field Crop Reporting Series provides estimates on seeded and harvested areas, yield and production. This is a series of five data collection activities where three occasions provide preliminary data for seeded areas (March) or production (July and September), and November provides final area and production estimates. This article examines the differences between the preliminary and final estimates for field crop statistics. The field crops included in this study are canola, all wheat, soybeans, barley, oats and corn for grain. The data from 2008-2018 are used for seeded area estimates while production estimates cover 2008-2017.

    Release date: 2018-11-08

  • Articles and reports: 11-626-X2017077
    Description:

    On April 13, 2017, the Government of Canada tabled legislation to legalize the recreational use of cannabis by adults. This will directly impact Canada’s statistical system. The focus of this Economic Insights article is to provide experimental estimates for the volume of cannabis consumption, based on existing information on the prevalence of cannabis use. The article presents experimental estimates of the number of tonnes of cannabis consumed by age group for the period from 1960 to 2015. The experimental estimates rely on survey data from multiple sources, statistical techniques to link the sources over time, and assumptions about consumption behaviour. They are subject to revision as improved or additional data sources become available.

    Release date: 2017-12-18

  • Articles and reports: 11-621-M2016101
    Description:

    Using data from the Monthly Retail Trade survey, this article discusses the measurement of online retail sales in the retail trade sector.

    Release date: 2016-11-14

  • Articles and reports: 12-001-X201600114544
    Description:

    In the Netherlands, statistical information about income and wealth is based on two large scale household panels that are completely derived from administrative data. A problem with using households as sampling units in the sample design of panels is the instability of these units over time. Changes in the household composition affect the inclusion probabilities required for design-based and model-assisted inference procedures. Such problems are circumvented in the two aforementioned household panels by sampling persons, who are followed over time. At each period the household members of these sampled persons are included in the sample. This is equivalent to sampling with probabilities proportional to household size where households can be selected more than once but with a maximum equal to the number of household members. In this paper properties of this sample design are described and contrasted with the Generalized Weight Share method for indirect sampling (Lavallée 1995, 2007). Methods are illustrated with an application to the Dutch Regional Income Survey.

    Release date: 2016-06-22

  • Articles and reports: 12-001-X201600114545
    Description:

    The estimation of quantiles is an important topic not only in the regression framework, but also in sampling theory. A natural alternative or addition to quantiles are expectiles. Expectiles as a generalization of the mean have become popular during the last years as they not only give a more detailed picture of the data than the ordinary mean, but also can serve as a basis to calculate quantiles by using their close relationship. We show, how to estimate expectiles under sampling with unequal probabilities and how expectiles can be used to estimate the distribution function. The resulting fitted distribution function estimator can be inverted leading to quantile estimates. We run a simulation study to investigate and compare the efficiency of the expectile based estimator.

    Release date: 2016-06-22

  • Articles and reports: 12-001-X201600114546
    Description:

    Adjusting the base weights using weighting classes is a standard approach for dealing with unit nonresponse. A common approach is to create nonresponse adjustments that are weighted by the inverse of the assumed response propensity of respondents within weighting classes under a quasi-randomization approach. Little and Vartivarian (2003) questioned the value of weighting the adjustment factor. In practice the models assumed are misspecified, so it is critical to understand the impact of weighting might have in this case. This paper describes the effects on nonresponse adjusted estimates of means and totals for population and domains computed using the weighted and unweighted inverse of the response propensities in stratified simple random sample designs. The performance of these estimators under different conditions such as different sample allocation, response mechanism, and population structure is evaluated. The findings show that for the scenarios considered the weighted adjustment has substantial advantages for estimating totals and using an unweighted adjustment may lead to serious biases except in very limited cases. Furthermore, unlike the unweighted estimates, the weighted estimates are not sensitive to how the sample is allocated.

    Release date: 2016-06-22

  • Stats in brief: 11-627-M2016002
    Description:

    The infographic is called Demographic Estimates, Census Metropolitan Areas – Canada, 2015 and is designed to inform readers about the latest demographic growth and aging trends at the Census Metropolitan Area (CMA) level.

    Release date: 2016-02-10

  • Articles and reports: 12-001-X201500214250
    Description:

    Assessing the impact of mode effects on survey estimates has become a crucial research objective due to the increasing use of mixed-mode designs. Despite the advantages of a mixed-mode design, such as lower costs and increased coverage, there is sufficient evidence that mode effects may be large relative to the precision of a survey. They may lead to incomparable statistics in time or over population subgroups and they may increase bias. Adaptive survey designs offer a flexible mathematical framework to obtain an optimal balance between survey quality and costs. In this paper, we employ adaptive designs in order to minimize mode effects. We illustrate our optimization model by means of a case-study on the Dutch Labor Force Survey. We focus on item-dependent mode effects and we evaluate the impact on survey quality by comparison to a gold standard.

    Release date: 2015-12-17
Reference (8)

Reference (8) ((8 results))

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