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All (6) ((6 results))

  • Articles and reports: 89-648-X2016001
    Description:

    Linkages between survey and administrative data are an increasingly common practice, due in part to the reduced burden to respondents, and to the data that can be obtained at a relatively low cost. Historical linkage, or the linkage of administrative data from previous years to the year of the survey, compounds these benefits by providing additional years of data. This paper examines the Longitudinal and International Study of Adults (LISA), which was linked to historical tax data on personal income tax returns (T1) and those collected from employers’ files (T4), among others not mentioned in this paper. It presents trends in historical linkage rates, compares the coherence of administrative data between the T1 and T4, presents the ability to use the data to create balanced panels, and uses the T1 data to produce age-earnings profiles by sex. The results show that the historical linkage rate is high (over 90% in most cases) and stable over time for respondents who are likely to file a tax return, and that the T1 and T4 administrative sources show similar earnings. Moreover, long balanced panels of up to 30 years in length (at the time of writing) can be created using LISA administrative linkage data.

    Release date: 2016-08-18

  • Articles and reports: 11-522-X201700014709
    Description:

    Traffic congestion is not limited to large cities but is also becoming a problem in medium-size cities and to roads going through cities. Among a large variety of congestion measures, six were selected for the ease of aggregation and their capacity to use the instantaneous information from CVUS-light component in 2014. From the selected measures, the Index of Congestion is potentially the only one not biased. This measure is used to illustrate different dimension of congestion on the road network.

    Release date: 2016-03-24

  • Articles and reports: 11-522-X201700014744
    Description:

    This presentation will begin with Dr. West providing a summary of research that has been conducted on the quality and utility of paradata collected as part of the United States National Survey of Family Growth (NSFG). The NSFG is the major national fertility survey in the U.S., and an important source of data on sexual activity, sexual behavior, and reproductive health for policy makers. For many years, the NSFG has been collecting various forms of paradata, including keystroke information (e.g., Couper and Kreuter 2013), call record information, detailed case disposition information, and interviewer observations related to key NSFG measures (e.g., West 2013). Dr. West will discuss some of the challenges of working with these data, in addition to evidence of their utility for nonresponse adjustment, interviewer evaluation, and/or responsive survey design purposes. Dr. Kreuter will then present research done using paradata collected as part of two panel surveys: the Medical Expenditure Panel Survey (MEPS) in the United States, and the Panel Labour Market and Social Security (PASS) in Germany. In both surveys, information from contacts in prior waves were experimentally used to improve contact and response rates in subsequent waves. In addition, research from PASS will be presented where interviewer observations on key outcome variables were collected to be used in nonresponse adjustment or responsive survey design decisions. Dr. Kreuter will not only present the research results but also the practical challenges in implementing the collection and use of both sets of paradata.

    Release date: 2016-03-24

  • Articles and reports: 11-522-X201700014746
    Description:

    Paradata research has focused on identifying opportunities for strategic improvement in data collection that could be operationally viable and lead to enhancements in quality or cost efficiency. To that end, Statistics Canada has developed and implemented a responsive collection design (RCD) strategy for computer-assisted telephone interview (CATI) household surveys to maximize quality and efficiency and to potentially reduce costs. RCD is an adaptive approach to survey data collection that uses information available prior to and during data collection to adjust the collection strategy for the remaining in-progress cases. In practice, the survey managers monitor and analyze collection progress against a predetermined set of indicators for two purposes: to identify critical data-collection milestones that require significant changes to the collection approach and to adjust collection strategies to make the most efficient use of remaining available resources. In the RCD context, numerous considerations come into play when determining which aspects of data collection to adjust and how to adjust them. Paradata sources play a key role in the planning, development and implementation of active management for RCD surveys. Since 2009, Statistics Canada has conducted several RCD surveys. This paper describes Statistics Canada’s experiences in implementing and monitoring this type of surveys.

    Release date: 2016-03-24

  • Articles and reports: 11-522-X201700014752
    Description:

    This paper presents a new price index method for processing electronic transaction (scanner) data. Price indices are calculated as a ratio of a turnover index and a weighted quantity index. Product weights of quantities sold are computed from the deflated prices of each month in the current publication year. New products can be timely incorporated without price imputations, so that all transactions can be processed. Product weights are monthly updated and are used to calculate direct indices with respect to a fixed base month. Price indices are free of chain drift by this construction. The results are robust under departures from the methodological choices. The method is part of the Dutch CPI since January 2016, when it was first applied to mobile phones.

    Release date: 2016-03-24

  • Articles and reports: 11-522-X201700014753
    Description:

    The fact that the world is in continuous change and that new technologies are becoming widely available creates new opportunities and challenges for National Statistical Institutes (NSIs) worldwide. What if NSIs could access vast amounts of sophisticated data for free (or for a low cost) from enterprises? Could this facilitate the possibility for NSIs to disseminate more accurate indicators for the policy-makers and users, significantly reduce the response burden for companies, reduce costs for the NSIs and in the long run improve the living standards of the people in a country? The time has now come for NSIs to find the best practice to align legislation, regulations and practices in relation to scanner data and big data. Without common ground, the prospect of reaching consensus is unlikely. The discussions need to start with how to define quality. If NSIs define and approach quality differently, this will lead to a highly undesirable situation, as NSIs will move further away from harmonisation. Sweden was one of the leading countries that put these issues on the agenda for European cooperation; in 2012 Sweden implemented scanner data in the national Consumer Price Index after it was proven through research studies and statistical analyses that scanner data was significantly better than the manually collected data.

    Release date: 2016-03-24
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Articles and reports (6)

Articles and reports (6) ((6 results))

  • Articles and reports: 89-648-X2016001
    Description:

    Linkages between survey and administrative data are an increasingly common practice, due in part to the reduced burden to respondents, and to the data that can be obtained at a relatively low cost. Historical linkage, or the linkage of administrative data from previous years to the year of the survey, compounds these benefits by providing additional years of data. This paper examines the Longitudinal and International Study of Adults (LISA), which was linked to historical tax data on personal income tax returns (T1) and those collected from employers’ files (T4), among others not mentioned in this paper. It presents trends in historical linkage rates, compares the coherence of administrative data between the T1 and T4, presents the ability to use the data to create balanced panels, and uses the T1 data to produce age-earnings profiles by sex. The results show that the historical linkage rate is high (over 90% in most cases) and stable over time for respondents who are likely to file a tax return, and that the T1 and T4 administrative sources show similar earnings. Moreover, long balanced panels of up to 30 years in length (at the time of writing) can be created using LISA administrative linkage data.

    Release date: 2016-08-18

  • Articles and reports: 11-522-X201700014709
    Description:

    Traffic congestion is not limited to large cities but is also becoming a problem in medium-size cities and to roads going through cities. Among a large variety of congestion measures, six were selected for the ease of aggregation and their capacity to use the instantaneous information from CVUS-light component in 2014. From the selected measures, the Index of Congestion is potentially the only one not biased. This measure is used to illustrate different dimension of congestion on the road network.

    Release date: 2016-03-24

  • Articles and reports: 11-522-X201700014744
    Description:

    This presentation will begin with Dr. West providing a summary of research that has been conducted on the quality and utility of paradata collected as part of the United States National Survey of Family Growth (NSFG). The NSFG is the major national fertility survey in the U.S., and an important source of data on sexual activity, sexual behavior, and reproductive health for policy makers. For many years, the NSFG has been collecting various forms of paradata, including keystroke information (e.g., Couper and Kreuter 2013), call record information, detailed case disposition information, and interviewer observations related to key NSFG measures (e.g., West 2013). Dr. West will discuss some of the challenges of working with these data, in addition to evidence of their utility for nonresponse adjustment, interviewer evaluation, and/or responsive survey design purposes. Dr. Kreuter will then present research done using paradata collected as part of two panel surveys: the Medical Expenditure Panel Survey (MEPS) in the United States, and the Panel Labour Market and Social Security (PASS) in Germany. In both surveys, information from contacts in prior waves were experimentally used to improve contact and response rates in subsequent waves. In addition, research from PASS will be presented where interviewer observations on key outcome variables were collected to be used in nonresponse adjustment or responsive survey design decisions. Dr. Kreuter will not only present the research results but also the practical challenges in implementing the collection and use of both sets of paradata.

    Release date: 2016-03-24

  • Articles and reports: 11-522-X201700014746
    Description:

    Paradata research has focused on identifying opportunities for strategic improvement in data collection that could be operationally viable and lead to enhancements in quality or cost efficiency. To that end, Statistics Canada has developed and implemented a responsive collection design (RCD) strategy for computer-assisted telephone interview (CATI) household surveys to maximize quality and efficiency and to potentially reduce costs. RCD is an adaptive approach to survey data collection that uses information available prior to and during data collection to adjust the collection strategy for the remaining in-progress cases. In practice, the survey managers monitor and analyze collection progress against a predetermined set of indicators for two purposes: to identify critical data-collection milestones that require significant changes to the collection approach and to adjust collection strategies to make the most efficient use of remaining available resources. In the RCD context, numerous considerations come into play when determining which aspects of data collection to adjust and how to adjust them. Paradata sources play a key role in the planning, development and implementation of active management for RCD surveys. Since 2009, Statistics Canada has conducted several RCD surveys. This paper describes Statistics Canada’s experiences in implementing and monitoring this type of surveys.

    Release date: 2016-03-24

  • Articles and reports: 11-522-X201700014752
    Description:

    This paper presents a new price index method for processing electronic transaction (scanner) data. Price indices are calculated as a ratio of a turnover index and a weighted quantity index. Product weights of quantities sold are computed from the deflated prices of each month in the current publication year. New products can be timely incorporated without price imputations, so that all transactions can be processed. Product weights are monthly updated and are used to calculate direct indices with respect to a fixed base month. Price indices are free of chain drift by this construction. The results are robust under departures from the methodological choices. The method is part of the Dutch CPI since January 2016, when it was first applied to mobile phones.

    Release date: 2016-03-24

  • Articles and reports: 11-522-X201700014753
    Description:

    The fact that the world is in continuous change and that new technologies are becoming widely available creates new opportunities and challenges for National Statistical Institutes (NSIs) worldwide. What if NSIs could access vast amounts of sophisticated data for free (or for a low cost) from enterprises? Could this facilitate the possibility for NSIs to disseminate more accurate indicators for the policy-makers and users, significantly reduce the response burden for companies, reduce costs for the NSIs and in the long run improve the living standards of the people in a country? The time has now come for NSIs to find the best practice to align legislation, regulations and practices in relation to scanner data and big data. Without common ground, the prospect of reaching consensus is unlikely. The discussions need to start with how to define quality. If NSIs define and approach quality differently, this will lead to a highly undesirable situation, as NSIs will move further away from harmonisation. Sweden was one of the leading countries that put these issues on the agenda for European cooperation; in 2012 Sweden implemented scanner data in the national Consumer Price Index after it was proven through research studies and statistical analyses that scanner data was significantly better than the manually collected data.

    Release date: 2016-03-24
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