History and context

Filter results by

Search Help
Currently selected filters that can be removed

Keyword(s)

Survey or statistical program

1 facets displayed. 0 facets selected.

Content

1 facets displayed. 0 facets selected.
Sort Help
entries

Results

All (5)

All (5) ((5 results))

  • Articles and reports: 75F0002M2014003
    Description:

    In order to provide a holographic or complete picture of low income, Statistics Canada uses three complementary low income lines: the Low Income Cut-offs (LICOs), the Low Income Measures (LIMs) and the Market Basket Measure (MBM). While the first two lines were developed by Statistics Canada, the MBM is based on concepts developed by Employment and Social Development Canada. Though these measures differ from one another, they give a generally consistent picture of low income status over time. None of these measures is the best. Each contributes its own perspective and its own strengths to the study of low income, so that cumulatively, the three provide a better understanding of the phenomenon of low income as a whole. These measures are not measures of poverty, but strictly measures of low income.

    Release date: 2014-12-10

  • Surveys and statistical programs – Documentation: 13-605-X201400514088
    Description:

    An overview of the Canadian Government Finance Statistics (CGFS) framework; how it relates to other government statistics such as the Canadian System of Macroeconomic Accounts and the Public Accounts; and the new GFS data products available to users

    Release date: 2014-11-07

  • Notices and consultations: 13-605-X201400414107
    Description:

    Beginning in November 2014, International Trade in goods data will be provided on a Balance of Payments (BOP) basis for additional country detail. In publishing this data, BOP-based exports to and imports from 27 countries, referred to as Canada’s Principal Trading Partners (PTPs), will be highlighted for the first time. BOP-based trade in goods data will be available for countries such as China and Mexico, Brazil and India, South Korea, and our largest European Union trading partners, in response to substantial demand for information on these countries in recent years. Until now, Canada’s geographical trading patterns have been examined almost exclusively through analysis of Customs-based trade data. Moreover, BOP trade in goods data for these countries will be available alongside the now quarterly Trade in Services data as well as annual Foreign Direct Investment data for many of these Principal Trading Partners, facilitating country-level international trade and investment analysis using fully comparable data. The objective of this article is to introduce these new measures. This note will first walk users through the key BOP concepts, most importantly the concept of change in ownership. This will serve to familiarize analysts with the Balance of Payments framework for analyzing country-level data, in contrast to Customs-based trade data. Second, some preliminary analysis will be reviewed to illustrate the concepts, with provisional estimates for BOP-based trade with China serving as the principal example. Lastly, we will outline the expansion of quarterly trade in services to generate new estimates of trade for the PTPs and discuss future work in trade statistics.

    Release date: 2014-11-04

  • Surveys and statistical programs – Documentation: 13-605-X201400214100
    Description:

    Canadian international merchandise trade data are released monthly and may be revised in subsequent releases as new information becomes available. These data are released approximately 35 days following the close of the reference period and represent one of the timeliest economic indicators produced by Statistics Canada. Given their timeliness, some of the data are not received in time and need to be estimated or modelled. This is the case for imports and exports of crude petroleum and natural gas. More specifically, at the time of release, energy trade data are based on an incomplete set of information and are revised as Statistics Canada and National Energy Board information becomes available in the subsequent months. Due to the increasing importance of energy imports and exports and the timeliness of the data, the revisions to energy prices and volumes are having an increasingly significant impact on the monthly revision to Canada’s trade balance. This note explains how the estimates in the initial release are made when data sources are not yet available, and how the original data are adjusted in subsequent releases.

    Release date: 2014-10-03

  • Articles and reports: 12-001-X201300211883
    Description:

    The history of survey sampling, dating from the writings of A.N. Kiaer, has been remarkably controversial. First Kiaer himself had to struggle to convince his contemporaries that survey sampling itself was a legitimate procedure. He spent several decades in the attempt, and was an old man before survey sampling became a reputable activity. The first person to provide both a theoretical justification of survey sampling (in 1906) and a practical demonstration of its feasibility (in a survey conducted in Reading which was published in 1912) was A.L. Bowley. In 1925, the ISI meeting in Rome adopted a resolution giving acceptance to the use of both randomization and purposive sampling. Bowley used both. However the next two decades saw a steady tendency for randomization to become mandatory. In 1934 Jerzy Neyman used the relatively recent failure of a large purposive survey to ensure that subsequent sample surveys would need to employ random sampling only. He found apt pupils in M.H. Hansen, W.N. Hurwitz and W.G. Madow, who together published a definitive sampling textbook in 1953. This went effectively unchallenged for nearly two decades. In the 1970s, however, R.M. Royall and his coauthors did challenge the use of random sampling inference, and advocated that of model-based sampling instead. That in turn gave rise to the third major controversy within little more than a century. The present author, however, with several others, believes that both design-based and model-based inference have a useful part to play.

    Release date: 2014-01-15
Data (0)

Data (0) (0 results)

No content available at this time.

Analysis (2)

Analysis (2) ((2 results))

  • Articles and reports: 75F0002M2014003
    Description:

    In order to provide a holographic or complete picture of low income, Statistics Canada uses three complementary low income lines: the Low Income Cut-offs (LICOs), the Low Income Measures (LIMs) and the Market Basket Measure (MBM). While the first two lines were developed by Statistics Canada, the MBM is based on concepts developed by Employment and Social Development Canada. Though these measures differ from one another, they give a generally consistent picture of low income status over time. None of these measures is the best. Each contributes its own perspective and its own strengths to the study of low income, so that cumulatively, the three provide a better understanding of the phenomenon of low income as a whole. These measures are not measures of poverty, but strictly measures of low income.

    Release date: 2014-12-10

  • Articles and reports: 12-001-X201300211883
    Description:

    The history of survey sampling, dating from the writings of A.N. Kiaer, has been remarkably controversial. First Kiaer himself had to struggle to convince his contemporaries that survey sampling itself was a legitimate procedure. He spent several decades in the attempt, and was an old man before survey sampling became a reputable activity. The first person to provide both a theoretical justification of survey sampling (in 1906) and a practical demonstration of its feasibility (in a survey conducted in Reading which was published in 1912) was A.L. Bowley. In 1925, the ISI meeting in Rome adopted a resolution giving acceptance to the use of both randomization and purposive sampling. Bowley used both. However the next two decades saw a steady tendency for randomization to become mandatory. In 1934 Jerzy Neyman used the relatively recent failure of a large purposive survey to ensure that subsequent sample surveys would need to employ random sampling only. He found apt pupils in M.H. Hansen, W.N. Hurwitz and W.G. Madow, who together published a definitive sampling textbook in 1953. This went effectively unchallenged for nearly two decades. In the 1970s, however, R.M. Royall and his coauthors did challenge the use of random sampling inference, and advocated that of model-based sampling instead. That in turn gave rise to the third major controversy within little more than a century. The present author, however, with several others, believes that both design-based and model-based inference have a useful part to play.

    Release date: 2014-01-15
Reference (3)

Reference (3) ((3 results))

  • Surveys and statistical programs – Documentation: 13-605-X201400514088
    Description:

    An overview of the Canadian Government Finance Statistics (CGFS) framework; how it relates to other government statistics such as the Canadian System of Macroeconomic Accounts and the Public Accounts; and the new GFS data products available to users

    Release date: 2014-11-07

  • Notices and consultations: 13-605-X201400414107
    Description:

    Beginning in November 2014, International Trade in goods data will be provided on a Balance of Payments (BOP) basis for additional country detail. In publishing this data, BOP-based exports to and imports from 27 countries, referred to as Canada’s Principal Trading Partners (PTPs), will be highlighted for the first time. BOP-based trade in goods data will be available for countries such as China and Mexico, Brazil and India, South Korea, and our largest European Union trading partners, in response to substantial demand for information on these countries in recent years. Until now, Canada’s geographical trading patterns have been examined almost exclusively through analysis of Customs-based trade data. Moreover, BOP trade in goods data for these countries will be available alongside the now quarterly Trade in Services data as well as annual Foreign Direct Investment data for many of these Principal Trading Partners, facilitating country-level international trade and investment analysis using fully comparable data. The objective of this article is to introduce these new measures. This note will first walk users through the key BOP concepts, most importantly the concept of change in ownership. This will serve to familiarize analysts with the Balance of Payments framework for analyzing country-level data, in contrast to Customs-based trade data. Second, some preliminary analysis will be reviewed to illustrate the concepts, with provisional estimates for BOP-based trade with China serving as the principal example. Lastly, we will outline the expansion of quarterly trade in services to generate new estimates of trade for the PTPs and discuss future work in trade statistics.

    Release date: 2014-11-04

  • Surveys and statistical programs – Documentation: 13-605-X201400214100
    Description:

    Canadian international merchandise trade data are released monthly and may be revised in subsequent releases as new information becomes available. These data are released approximately 35 days following the close of the reference period and represent one of the timeliest economic indicators produced by Statistics Canada. Given their timeliness, some of the data are not received in time and need to be estimated or modelled. This is the case for imports and exports of crude petroleum and natural gas. More specifically, at the time of release, energy trade data are based on an incomplete set of information and are revised as Statistics Canada and National Energy Board information becomes available in the subsequent months. Due to the increasing importance of energy imports and exports and the timeliness of the data, the revisions to energy prices and volumes are having an increasingly significant impact on the monthly revision to Canada’s trade balance. This note explains how the estimates in the initial release are made when data sources are not yet available, and how the original data are adjusted in subsequent releases.

    Release date: 2014-10-03
Date modified: