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All (4)

All (4) ((4 results))

  • 1. Geographic Structures As Census Variables: Using Geography to Analyse Social and Economic Processes Archived
    Articles and reports: 92F0138M2001001
    Description:

    Traditionally, Statistics Canada uses standard geographic areas as "containers" for the dissemination of statistical data. However, geographic structures are often used as variables in general applications, for example, to document the rural and urban population in a specific area such as an incorporated municipality (census subdivision). They are not often cross-tabulated with each other to illustrate and analyse specific social and economic processes, for example, the settlement patterns of the population inside and outside of larger urban centres broken down by urban and rural areas.The introduction of the census metropolitan area and census agglomeration influenced zone (MIZ) concept presents additional opportunities to use geographic structures as variables to analyse census data.The objectives of this working paper are to illustrate the advantages of using geographic structures as variables to better analyse social and economic processes and to initiate a discussion in the user community about using these variables and the potential of this largely untapped capability of the Census databases. In order to achieve these objectives, four examples of geography as a variable are presented. The examples include Aboriginal persons living on-reserve and off-reserve in urban and rural areas in Canada, the unemployment rate of persons living in urban and rural areas in Canada, the gross rent of renter households in urban and rural areas in Canada, and the migration flows of persons 15 to 24 years of age between major urban centres and rural and small town areas (MIZ).Our intent is to encourage the use of geographic structures as census variables in order to provide users with the tools that will enable them to more accurately analyse the social and economic processes that take place in the geographic areas of Canada.

    Release date: 2001-03-16
  • 2. On the validity of Markov latent class analysis for estimating classification error in labor force data Archived
    Articles and reports: 12-001-X20000025534
    Description:

    The primary goal of this research is to investigate the validity of Markov latent class analysis (MLCA) estimates of labor force classification error and to evaluate the efficacy of MLC analysis as an alternative to traditional methods for evaluating data quality.

    Release date: 2001-02-28
  • 3. Modeling interviewer effects in panel surveys: An application Archived
    Articles and reports: 12-001-X20000025539
    Description:

    In this paper we will combine two applications of multilevel models. The multilevel model is suitable to analyze interviewer effects on survey data. It can also be used to analyze longitudinal - "repeated measurements" - data. We will analyze a data quality indicator of panel data that come from the Belgian Election Studies.

    Release date: 2001-02-28
  • 4. In Search of Intergenerational Credit Constraints Among Canadian Men: Quantile Versus Mean Regression Tests for Binding Credit Constraints Archived
    Articles and reports: 11F0019M2001158
    Geography: Canada
    Description:

    Several recent papers have cited non-linearities in the relationship between incomes of parents and their children as evidence of important intergenerational credit constraints. This paper argues that any pattern in the conditional expectation function can be justified by a properly constructed story with credit constraints. This raises questions about the validity of the approach. Quantile regressions provide an alternative test. Using data from Canadian tax files, this paper finds results contrary to the credit constraints hypothesis; the non-linearities in the regression function are driven by the low-ability (unconstrained) sons rather than high-ability (presumably constrained) sons.

    Release date: 2001-01-30
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Analysis (4)

Analysis (4) ((4 results))

  • 1. Geographic Structures As Census Variables: Using Geography to Analyse Social and Economic Processes Archived
    Articles and reports: 92F0138M2001001
    Description:

    Traditionally, Statistics Canada uses standard geographic areas as "containers" for the dissemination of statistical data. However, geographic structures are often used as variables in general applications, for example, to document the rural and urban population in a specific area such as an incorporated municipality (census subdivision). They are not often cross-tabulated with each other to illustrate and analyse specific social and economic processes, for example, the settlement patterns of the population inside and outside of larger urban centres broken down by urban and rural areas.The introduction of the census metropolitan area and census agglomeration influenced zone (MIZ) concept presents additional opportunities to use geographic structures as variables to analyse census data.The objectives of this working paper are to illustrate the advantages of using geographic structures as variables to better analyse social and economic processes and to initiate a discussion in the user community about using these variables and the potential of this largely untapped capability of the Census databases. In order to achieve these objectives, four examples of geography as a variable are presented. The examples include Aboriginal persons living on-reserve and off-reserve in urban and rural areas in Canada, the unemployment rate of persons living in urban and rural areas in Canada, the gross rent of renter households in urban and rural areas in Canada, and the migration flows of persons 15 to 24 years of age between major urban centres and rural and small town areas (MIZ).Our intent is to encourage the use of geographic structures as census variables in order to provide users with the tools that will enable them to more accurately analyse the social and economic processes that take place in the geographic areas of Canada.

    Release date: 2001-03-16
  • 2. On the validity of Markov latent class analysis for estimating classification error in labor force data Archived
    Articles and reports: 12-001-X20000025534
    Description:

    The primary goal of this research is to investigate the validity of Markov latent class analysis (MLCA) estimates of labor force classification error and to evaluate the efficacy of MLC analysis as an alternative to traditional methods for evaluating data quality.

    Release date: 2001-02-28
  • 3. Modeling interviewer effects in panel surveys: An application Archived
    Articles and reports: 12-001-X20000025539
    Description:

    In this paper we will combine two applications of multilevel models. The multilevel model is suitable to analyze interviewer effects on survey data. It can also be used to analyze longitudinal - "repeated measurements" - data. We will analyze a data quality indicator of panel data that come from the Belgian Election Studies.

    Release date: 2001-02-28
  • 4. In Search of Intergenerational Credit Constraints Among Canadian Men: Quantile Versus Mean Regression Tests for Binding Credit Constraints Archived
    Articles and reports: 11F0019M2001158
    Geography: Canada
    Description:

    Several recent papers have cited non-linearities in the relationship between incomes of parents and their children as evidence of important intergenerational credit constraints. This paper argues that any pattern in the conditional expectation function can be justified by a properly constructed story with credit constraints. This raises questions about the validity of the approach. Quantile regressions provide an alternative test. Using data from Canadian tax files, this paper finds results contrary to the credit constraints hypothesis; the non-linearities in the regression function are driven by the low-ability (unconstrained) sons rather than high-ability (presumably constrained) sons.

    Release date: 2001-01-30
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