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  • Articles and reports: 89-653-X2018001
    Description:

    This Concepts and Methods Guide is intended to provide a detailed review of the 2017 APS with respect to its subject matter and methodological approaches. It is designed to assist APS data users by serving as a guide to the concepts and measures of the survey as well as the technical details of the survey's design, field work and data processing. This guide is meant to provide users with helpful information on how to use and interpret survey results. The discussion on data quality also allows users to review the strengths and limitations of the data for their particular needs.

    Chapter 1 of this guide provides an overview of the 2017 APS by introducing the survey's background and objectives. Chapter 2 outlines the survey's themes and explains the key concepts and definitions used for the survey. Chapters 3 to 6 cover important aspects of the APS survey methodology, sampling design, data collection and processing. Chapters 7 and 8 review issues of data quality and caution users about comparing 2017 APS data with data from other sources. Chapter 9 outlines the survey products available to the public, including data tables, analytical articles and reference material. The Appendices provide a comprehensive list of survey indicators, extra coding categories and standard classifications used on the APS. Lastly, a glossary of survey terms is also provided.

    Release date: 2018-11-26

  • Articles and reports: 82-003-X201801100003
    Description:

    This study describes the size and age structure of the Canadian veteran population forecasted by Veterans Affairs Canada. Veteran health was examined for two eras of Regular Force veterans. The health of earlier-era veterans (released between 1954 and 2003) was examined using the 2003 Canadian Community Health Survey. The health of recent-era veterans (released between 1998 and 2012) was examined using the 2013 Life After Service Survey. Health indicators for veterans were compared with the Canadian general population.

    Release date: 2018-11-21

  • Articles and reports: 89-28-0001201800100008
    Description:

    This edition presents changes in new home prices for Canada and select census metropolitan areas (CMAs) between August 2017 and August 2018. During this period, Canadians experienced rising mortgage rates, tighter lending rules and some provincial policy interventions.

    Release date: 2018-10-31

  • Articles and reports: 62F0014M2018002
    Description:

    This article offers highlights on the recent trends in the new house prices in the Greater Golden Horseshoe region, for the six census metropolitan areas surveyed for the New Housing Price Index. 

    Release date: 2018-08-09

  • Articles and reports: 12-001-X201800154963
    Description:

    The probability-sampling-based framework has dominated survey research because it provides precise mathematical tools to assess sampling variability. However increasing costs and declining response rates are expanding the use of non-probability samples, particularly in general population settings, where samples of individuals pulled from web surveys are becoming increasingly cheap and easy to access. But non-probability samples are at risk for selection bias due to differential access, degrees of interest, and other factors. Calibration to known statistical totals in the population provide a means of potentially diminishing the effect of selection bias in non-probability samples. Here we show that model calibration using adaptive LASSO can yield a consistent estimator of a population total as long as a subset of the true predictors is included in the prediction model, thus allowing large numbers of possible covariates to be included without risk of overfitting. We show that the model calibration using adaptive LASSO provides improved estimation with respect to mean square error relative to standard competitors such as generalized regression (GREG) estimators when a large number of covariates are required to determine the true model, with effectively no loss in efficiency over GREG when smaller models will suffice. We also derive closed form variance estimators of population totals, and compare their behavior with bootstrap estimators. We conclude with a real world example using data from the National Health Interview Survey.

    Release date: 2018-06-21

  • Articles and reports: 12-001-X201700254871
    Description:

    In this paper the question is addressed how alternative data sources, such as administrative and social media data, can be used in the production of official statistics. Since most surveys at national statistical institutes are conducted repeatedly over time, a multivariate structural time series modelling approach is proposed to model the series observed by a repeated surveys with related series obtained from such alternative data sources. Generally, this improves the precision of the direct survey estimates by using sample information observed in preceding periods and information from related auxiliary series. This model also makes it possible to utilize the higher frequency of the social media to produce more precise estimates for the sample survey in real time at the moment that statistics for the social media become available but the sample data are not yet available. The concept of cointegration is applied to address the question to which extent the alternative series represent the same phenomena as the series observed with the repeated survey. The methodology is applied to the Dutch Consumer Confidence Survey and a sentiment index derived from social media.

    Release date: 2017-12-21

  • Articles and reports: 12-001-X201700114819
    Description:

    Structural time series models are a powerful technique for variance reduction in the framework of small area estimation (SAE) based on repeatedly conducted surveys. Statistics Netherlands implemented a structural time series model to produce monthly figures about the labour force with the Dutch Labour Force Survey (DLFS). Such models, however, contain unknown hyperparameters that have to be estimated before the Kalman filter can be launched to estimate state variables of the model. This paper describes a simulation aimed at studying the properties of hyperparameter estimators in the model. Simulating distributions of the hyperparameter estimators under different model specifications complements standard model diagnostics for state space models. Uncertainty around the model hyperparameters is another major issue. To account for hyperparameter uncertainty in the mean squared errors (MSE) estimates of the DLFS, several estimation approaches known in the literature are considered in a simulation. Apart from the MSE bias comparison, this paper also provides insight into the variances and MSEs of the MSE estimators considered.

    Release date: 2017-06-22

  • Articles and reports: 12-001-X201700114820
    Description:

    Measurement errors can induce bias in the estimation of transitions, leading to erroneous conclusions about labour market dynamics. Traditional literature on gross flows estimation is based on the assumption that measurement errors are uncorrelated over time. This assumption is not realistic in many contexts, because of survey design and data collection strategies. In this work, we use a model-based approach to correct observed gross flows from classification errors with latent class Markov models. We refer to data collected with the Italian Continuous Labour Force Survey, which is cross-sectional, quarterly, with a 2-2-2 rotating design. The questionnaire allows us to use multiple indicators of labour force conditions for each quarter: two collected in the first interview, and a third collected one year later. Our approach provides a method to estimate labour market mobility, taking into account correlated errors and the rotating design of the survey. The best-fitting model is a mixed latent class Markov model with covariates affecting latent transitions and correlated errors among indicators; the mixture components are of mover-stayer type. The better fit of the mixture specification is due to more accurately estimated latent transitions.

    Release date: 2017-06-22

  • Articles and reports: 89-657-X2016002
    Geography: Census metropolitan area
    Description:

    This study examines the settlement patterns of the immigrant population as well as certain social integration components. It starts by outlining recent trends in the settlement patterns of the immigrant population in Canadian census metropolitan areas, namely Toronto, Montréal and Vancouver. Based on data from the 2013 General Social Survey on Social Identity, it then looks at residence characteristics, such as type of municipality and concentration of immigrant population, according to four social integration components: personal network characteristics, relationships with neighbours, social participation and involvement in community activities, and sense of belonging.

    Release date: 2017-05-08

  • Articles and reports: 82-003-X201700314781
    Description:

    This study describes residential exposure to ambient fine particulate matter, by visible minority, immigrant and socioeconomic status in Canada, while stratifying the analysis across the urban-rural divide.

    Release date: 2017-03-15
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Articles and reports (128)

Articles and reports (128) (0 to 10 of 128 results)

  • Articles and reports: 89-653-X2018001
    Description:

    This Concepts and Methods Guide is intended to provide a detailed review of the 2017 APS with respect to its subject matter and methodological approaches. It is designed to assist APS data users by serving as a guide to the concepts and measures of the survey as well as the technical details of the survey's design, field work and data processing. This guide is meant to provide users with helpful information on how to use and interpret survey results. The discussion on data quality also allows users to review the strengths and limitations of the data for their particular needs.

    Chapter 1 of this guide provides an overview of the 2017 APS by introducing the survey's background and objectives. Chapter 2 outlines the survey's themes and explains the key concepts and definitions used for the survey. Chapters 3 to 6 cover important aspects of the APS survey methodology, sampling design, data collection and processing. Chapters 7 and 8 review issues of data quality and caution users about comparing 2017 APS data with data from other sources. Chapter 9 outlines the survey products available to the public, including data tables, analytical articles and reference material. The Appendices provide a comprehensive list of survey indicators, extra coding categories and standard classifications used on the APS. Lastly, a glossary of survey terms is also provided.

    Release date: 2018-11-26

  • Articles and reports: 82-003-X201801100003
    Description:

    This study describes the size and age structure of the Canadian veteran population forecasted by Veterans Affairs Canada. Veteran health was examined for two eras of Regular Force veterans. The health of earlier-era veterans (released between 1954 and 2003) was examined using the 2003 Canadian Community Health Survey. The health of recent-era veterans (released between 1998 and 2012) was examined using the 2013 Life After Service Survey. Health indicators for veterans were compared with the Canadian general population.

    Release date: 2018-11-21

  • Articles and reports: 89-28-0001201800100008
    Description:

    This edition presents changes in new home prices for Canada and select census metropolitan areas (CMAs) between August 2017 and August 2018. During this period, Canadians experienced rising mortgage rates, tighter lending rules and some provincial policy interventions.

    Release date: 2018-10-31

  • Articles and reports: 62F0014M2018002
    Description:

    This article offers highlights on the recent trends in the new house prices in the Greater Golden Horseshoe region, for the six census metropolitan areas surveyed for the New Housing Price Index. 

    Release date: 2018-08-09

  • Articles and reports: 12-001-X201800154963
    Description:

    The probability-sampling-based framework has dominated survey research because it provides precise mathematical tools to assess sampling variability. However increasing costs and declining response rates are expanding the use of non-probability samples, particularly in general population settings, where samples of individuals pulled from web surveys are becoming increasingly cheap and easy to access. But non-probability samples are at risk for selection bias due to differential access, degrees of interest, and other factors. Calibration to known statistical totals in the population provide a means of potentially diminishing the effect of selection bias in non-probability samples. Here we show that model calibration using adaptive LASSO can yield a consistent estimator of a population total as long as a subset of the true predictors is included in the prediction model, thus allowing large numbers of possible covariates to be included without risk of overfitting. We show that the model calibration using adaptive LASSO provides improved estimation with respect to mean square error relative to standard competitors such as generalized regression (GREG) estimators when a large number of covariates are required to determine the true model, with effectively no loss in efficiency over GREG when smaller models will suffice. We also derive closed form variance estimators of population totals, and compare their behavior with bootstrap estimators. We conclude with a real world example using data from the National Health Interview Survey.

    Release date: 2018-06-21

  • Articles and reports: 12-001-X201700254871
    Description:

    In this paper the question is addressed how alternative data sources, such as administrative and social media data, can be used in the production of official statistics. Since most surveys at national statistical institutes are conducted repeatedly over time, a multivariate structural time series modelling approach is proposed to model the series observed by a repeated surveys with related series obtained from such alternative data sources. Generally, this improves the precision of the direct survey estimates by using sample information observed in preceding periods and information from related auxiliary series. This model also makes it possible to utilize the higher frequency of the social media to produce more precise estimates for the sample survey in real time at the moment that statistics for the social media become available but the sample data are not yet available. The concept of cointegration is applied to address the question to which extent the alternative series represent the same phenomena as the series observed with the repeated survey. The methodology is applied to the Dutch Consumer Confidence Survey and a sentiment index derived from social media.

    Release date: 2017-12-21

  • Articles and reports: 12-001-X201700114819
    Description:

    Structural time series models are a powerful technique for variance reduction in the framework of small area estimation (SAE) based on repeatedly conducted surveys. Statistics Netherlands implemented a structural time series model to produce monthly figures about the labour force with the Dutch Labour Force Survey (DLFS). Such models, however, contain unknown hyperparameters that have to be estimated before the Kalman filter can be launched to estimate state variables of the model. This paper describes a simulation aimed at studying the properties of hyperparameter estimators in the model. Simulating distributions of the hyperparameter estimators under different model specifications complements standard model diagnostics for state space models. Uncertainty around the model hyperparameters is another major issue. To account for hyperparameter uncertainty in the mean squared errors (MSE) estimates of the DLFS, several estimation approaches known in the literature are considered in a simulation. Apart from the MSE bias comparison, this paper also provides insight into the variances and MSEs of the MSE estimators considered.

    Release date: 2017-06-22

  • Articles and reports: 12-001-X201700114820
    Description:

    Measurement errors can induce bias in the estimation of transitions, leading to erroneous conclusions about labour market dynamics. Traditional literature on gross flows estimation is based on the assumption that measurement errors are uncorrelated over time. This assumption is not realistic in many contexts, because of survey design and data collection strategies. In this work, we use a model-based approach to correct observed gross flows from classification errors with latent class Markov models. We refer to data collected with the Italian Continuous Labour Force Survey, which is cross-sectional, quarterly, with a 2-2-2 rotating design. The questionnaire allows us to use multiple indicators of labour force conditions for each quarter: two collected in the first interview, and a third collected one year later. Our approach provides a method to estimate labour market mobility, taking into account correlated errors and the rotating design of the survey. The best-fitting model is a mixed latent class Markov model with covariates affecting latent transitions and correlated errors among indicators; the mixture components are of mover-stayer type. The better fit of the mixture specification is due to more accurately estimated latent transitions.

    Release date: 2017-06-22

  • Articles and reports: 89-657-X2016002
    Geography: Census metropolitan area
    Description:

    This study examines the settlement patterns of the immigrant population as well as certain social integration components. It starts by outlining recent trends in the settlement patterns of the immigrant population in Canadian census metropolitan areas, namely Toronto, Montréal and Vancouver. Based on data from the 2013 General Social Survey on Social Identity, it then looks at residence characteristics, such as type of municipality and concentration of immigrant population, according to four social integration components: personal network characteristics, relationships with neighbours, social participation and involvement in community activities, and sense of belonging.

    Release date: 2017-05-08

  • Articles and reports: 82-003-X201700314781
    Description:

    This study describes residential exposure to ambient fine particulate matter, by visible minority, immigrant and socioeconomic status in Canada, while stratifying the analysis across the urban-rural divide.

    Release date: 2017-03-15
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