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- 1. User Guide - Survey of Household Spending, 2000 ArchivedSurveys and statistical programs – Documentation: 62F0026M2001004Geography: Province or territoryDescription:
This guide presents information of interest to users of data from the Survey of Household Spending. Data are collected via personal interview conducted in January, February and March after the reference year using a paper questionnaire. Information is gathered about the spending habits, dwelling characteristics and household equipment of Canadian households during the reference year. The survey covers private households in the ten provinces. (The three territories are surveyed every second year starting in 2001.)
This guide includes definitions of survey terms and variables, as well as descriptions of survey methodology and data quality. There is also a section describing the various statistics that can be created using expenditure data (e.g., budget share, market share, and aggregates).
Release date: 2001-12-12 - Surveys and statistical programs – Documentation: 62F0026M2001001Description:
This report describes the quality indicators produced for the 1998 Survey of Household Spending. It covers the usual quality indicators that help users interpret data, such as coefficients of variation, nonresponse rates, imputation rates and the impact of imputed data on the estimates. Added to these are various less often used indicators such as slippage rates and measures of the representativity of the sample for particular characteristics that are useful for evaluating the survey methodology.
Release date: 2001-10-15 - Surveys and statistical programs – Documentation: 62F0026M2001002Description:
This report describes the quality indicators produced for the 1999 Survey of Household Spending. It covers the usual quality indicators that help users interpret data, such as coefficients of variation, nonresponse rates, imputation rates and the impact of imputed data on the estimates. Added to these are various less often used indicators such as slippage rates and measures of the representativity of the sample for particular characteristics that are useful for evaluating the survey methodology.
Release date: 2001-10-15 - 4. Methodology of the Survey of Household Spending ArchivedSurveys and statistical programs – Documentation: 62F0026M2001003Description:
This document provides a detailed description of the methodology of the Survey of Household Spending. Topics covered include: target population; sample design; data collection; data processing; weighting and estimation; estimation of sampling error; and data suppression and confidentiality.
Release date: 2001-10-15 - 5. An Assessment of EI and SA Reporting in SLID ArchivedArticles and reports: 11F0019M2001166Geography: CanadaDescription:
This study assesses two potential problems with respect to the reporting of Employment Insurance (EI) and Social Assistance (SA) benefits in the Survey of Labour and Income Dynamics (SLID): (a) under-reporting of the monthly number of beneficiaries; and (b) a tendency to incorrectly report receiving benefits throughout the year, while in fact benefits may have been received only in certain months, leading to artificial spikes in the January starts and December terminations of benefit spells (seam effect). The results of the analysis show the following:
(1) The rate of under-reporting of EI in SLID is about 15%. Although it varies by month (from 0% to 30%), it is fairly stable from year to year.
(2) There are significant spikes in the number of January starts and December terminations of EI benefit spells. However, the spikes in January starts appear to represent a real phenomenon, rather than a seam problem. They mirror closely the pattern of establishment of new EI claims (the latter increase significantly in January as a result of the decline in employment following the Christmas peak demand). There are no corresponding statistics for EI claim terminations to assess the nature of December spikes.
(3) The rate of under-reporting of SA in SLID is about 50%, significantly greater than for EI. The rate of under-reporting goes down to about 20% to 30%, if we assume that those who received SA, but did not report in which months they received benefits, received benefits throughout the year.
(4) There are large spikes in the number of January starts and December terminations. As in the case of EI, the SA could reflect a real phenomenon. After all, SA starts and terminations are affected by labour market conditions, in the same way EI starts and terminations are affected. However, the SA spikes are much larger than the EI spikes, which increases the probability that, at least in part, are due to a seam effect.
Release date: 2001-09-11 - 6. Survey of Financial Security - Methodology for Estimating the Value of Employer Pension Plan Benefits ArchivedSurveys and statistical programs – Documentation: 13F0026M2001003Description:
Initial results from the Survey of Financial Security (SFS), which provides information on the net worth of Canadians, were released on March 15 2001, in The daily. The survey collected information on the value of the financial and non-financial assets owned by each family unit and on the amount of their debt.
Statistics Canada is currently refining this initial estimate of net worth by adding to it an estimate of the value of benefits accrued in employer pension plans. This is an important addition to any asset and debt survey as, for many family units, it is likely to be one of the largest assets. With the aging of the population, information on pension accumulations is greatly needed to better understand the financial situation of those nearing retirement. These updated estimates of the Survey of Financial Security will be released in late fall 2001.
The process for estimating the value of employer pension plan benefits is a complex one. This document describes the methodology for estimating that value, for the following groups: a) persons who belonged to an RPP at the time of the survey (referred to as current plan members); b) persons who had previously belonged to an RPP and either left the money in the plan or transferred it to a new plan; c) persons who are receiving RPP benefits.
This methodology was proposed by Hubert Frenken and Michael Cohen. The former has many years of experience with Statistics Canada working with data on employer pension plans; the latter is a principal with the actuarial consulting firm William M. Mercer. Earlier this year, Statistics Canada carried out a public consultation on the proposed methodology. This report includes updates made as a result of feedback received from data users.
Release date: 2001-09-05 - 7. Telesurvey methodologies for household surveys: A review and some thoughts for the future ArchivedArticles and reports: 12-001-X20010015851Description:
We consider 'telesurveys' as surveys in which the predominant or unique mode of collection is based on some means of electronic telecommunications - including both the telephone and other more advanced technological devices such as e-mail, Internet, videophone or fax. We review, briefly, the early history of telephone surveys, and, in more detail, recent developments in the areas of sample design and estimation, coverage and nonresponse and evaluation of data quality. All these methodological developments have led the telephone survey to become the major mode of collection in the sample survey field in the past quarter of a century. Other modes of advanced telecommunication are fast becoming important supplements and even competitors to the fixed line telephone and are already being used in various ways for sample surveys. We examine their potential for survey work and the possible impact of current and future technological developments of the communications industry on survey practice and their methodological implications.
Release date: 2001-08-22 - 8. Regression composite estimation for the Canadian Labour Force Survey with a rotating panel design ArchivedArticles and reports: 12-001-X20010015852Description:
We consider the regression composite estimation introduced by Singh (1994, 1996; termed earlier as "modified regression composite" estimation), a version of which (suggested by Fuller 1999) has been implemented for the Canadian Labour Force Survey (CLFS) beginning in January 2000. The regression composite (rc) estimator enhances the generalized regression (gr) estimator used earlier for the CLFS and the well known Gurney-Daly ak-composite estimator in several ways.
Release date: 2001-08-22 - Articles and reports: 12-001-X20010015853Description:
The Canadian Labour Force Survey is a monthly survey of households selected according to a stratified multistage design. The sample of households is divided into six panels (rotation groups). A panel remains in the sample for six consecutive months and is then dropped from the sample. In the past, a generalized regression estimator, based only on the current month's data, has been implemented with a regression weights program. In this paper, we study regression composite estimation procedures that make use of sample information from previous periods and that can be implemented with a regression weights program.
Release date: 2001-08-22 - Articles and reports: 12-001-X20010015854Description:
This paper looks at a range of estimators applicable to a regularly repeated household survey with controlled overlap between successive surveys. The paper shows how the Best Linear Unbiased Estimator (BLUE) based on a fixed window of time points can be improved by applying the technique of generalised regression. This improved estimator is compared to the AK estimator of Gurney and Daly (1965) and the modified regression estimator of Singh, Kennedy, Wu and Brisebois (1997), using data from the Australian Labour Force Survey.
Release date: 2001-08-22
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- 1. An Assessment of EI and SA Reporting in SLID ArchivedArticles and reports: 11F0019M2001166Geography: CanadaDescription:
This study assesses two potential problems with respect to the reporting of Employment Insurance (EI) and Social Assistance (SA) benefits in the Survey of Labour and Income Dynamics (SLID): (a) under-reporting of the monthly number of beneficiaries; and (b) a tendency to incorrectly report receiving benefits throughout the year, while in fact benefits may have been received only in certain months, leading to artificial spikes in the January starts and December terminations of benefit spells (seam effect). The results of the analysis show the following:
(1) The rate of under-reporting of EI in SLID is about 15%. Although it varies by month (from 0% to 30%), it is fairly stable from year to year.
(2) There are significant spikes in the number of January starts and December terminations of EI benefit spells. However, the spikes in January starts appear to represent a real phenomenon, rather than a seam problem. They mirror closely the pattern of establishment of new EI claims (the latter increase significantly in January as a result of the decline in employment following the Christmas peak demand). There are no corresponding statistics for EI claim terminations to assess the nature of December spikes.
(3) The rate of under-reporting of SA in SLID is about 50%, significantly greater than for EI. The rate of under-reporting goes down to about 20% to 30%, if we assume that those who received SA, but did not report in which months they received benefits, received benefits throughout the year.
(4) There are large spikes in the number of January starts and December terminations. As in the case of EI, the SA could reflect a real phenomenon. After all, SA starts and terminations are affected by labour market conditions, in the same way EI starts and terminations are affected. However, the SA spikes are much larger than the EI spikes, which increases the probability that, at least in part, are due to a seam effect.
Release date: 2001-09-11 - 2. Telesurvey methodologies for household surveys: A review and some thoughts for the future ArchivedArticles and reports: 12-001-X20010015851Description:
We consider 'telesurveys' as surveys in which the predominant or unique mode of collection is based on some means of electronic telecommunications - including both the telephone and other more advanced technological devices such as e-mail, Internet, videophone or fax. We review, briefly, the early history of telephone surveys, and, in more detail, recent developments in the areas of sample design and estimation, coverage and nonresponse and evaluation of data quality. All these methodological developments have led the telephone survey to become the major mode of collection in the sample survey field in the past quarter of a century. Other modes of advanced telecommunication are fast becoming important supplements and even competitors to the fixed line telephone and are already being used in various ways for sample surveys. We examine their potential for survey work and the possible impact of current and future technological developments of the communications industry on survey practice and their methodological implications.
Release date: 2001-08-22 - 3. Regression composite estimation for the Canadian Labour Force Survey with a rotating panel design ArchivedArticles and reports: 12-001-X20010015852Description:
We consider the regression composite estimation introduced by Singh (1994, 1996; termed earlier as "modified regression composite" estimation), a version of which (suggested by Fuller 1999) has been implemented for the Canadian Labour Force Survey (CLFS) beginning in January 2000. The regression composite (rc) estimator enhances the generalized regression (gr) estimator used earlier for the CLFS and the well known Gurney-Daly ak-composite estimator in several ways.
Release date: 2001-08-22 - Articles and reports: 12-001-X20010015853Description:
The Canadian Labour Force Survey is a monthly survey of households selected according to a stratified multistage design. The sample of households is divided into six panels (rotation groups). A panel remains in the sample for six consecutive months and is then dropped from the sample. In the past, a generalized regression estimator, based only on the current month's data, has been implemented with a regression weights program. In this paper, we study regression composite estimation procedures that make use of sample information from previous periods and that can be implemented with a regression weights program.
Release date: 2001-08-22 - Articles and reports: 12-001-X20010015854Description:
This paper looks at a range of estimators applicable to a regularly repeated household survey with controlled overlap between successive surveys. The paper shows how the Best Linear Unbiased Estimator (BLUE) based on a fixed window of time points can be improved by applying the technique of generalised regression. This improved estimator is compared to the AK estimator of Gurney and Daly (1965) and the modified regression estimator of Singh, Kennedy, Wu and Brisebois (1997), using data from the Australian Labour Force Survey.
Release date: 2001-08-22 - 6. Regression composite estimation for the Canadian Labour Force Survey: Evaluation and implementation ArchivedArticles and reports: 12-001-X20010015855Description:
The Canadian Labour Force Survey (LFS) is a monthly survey with a complex rotating panel design. After extensive studies, including the investigation of a number of alternative methods for exploiting the sample overlap to improve the quality of estimates, the LFS has chosen a composite estimation method which achieves this goal while satisfying practical constraints. In addition, for variables where there is a substantial gain in efficiency, the new time series tend to make more sense from a subject-matter perspective. This makes it easier to explain LFS estimates to users and the media. Because of the reduced variance under composite estimation, for some variables it is now possible to publish monthly estimates where only three-month moving averages were published in the past. In addition, a greater number of series can be successfully seasonally adjusted.
Release date: 2001-08-22 - 7. Variance estimation after imputation ArchivedArticles and reports: 12-001-X20010015856Description:
Imputation is commonly used to compensate for item nonresponse. Variance estimation after imputation has generated considerable discussion and several variance estimators have been proposed. We propose a variance estimator based on a pseudo data set used only for variance estimation. Standard complete data variance estimators applied to the pseudo data set lead to consistent estimators for linear estimators under various imputation methods, including without-replacement hot deck imputation and with-replacement hot deck imputation. The asymptotic equivalence of the proposed method and the adjusted jackknife method of Rao and Sitter (1995) is illustrated. The proposed method is directly applicable to variance estimation for two-phase sampling.
Release date: 2001-08-22 - 8. A multivariate technique for multiply imputing missing values using a sequence of regression models ArchivedArticles and reports: 12-001-X20010015857Description:
This article describes and evaluates a procedure for imputing missing values for a relatively complex data structure when the data are missing at random. The imputations are obtained by fitting a sequence of regression models and drawing values from the corresponding predictive distributions. The types of regression models used are linear, logistic, Poisson, generalized logit or a mixture of these depending on the type of variable being imputed. Two additional common features in the imputation process are incorporated: restriction to a relevant subpopulation for some variables and logical bounds or constraints for the imputed values. The restrictions involve subsetting the sample individuals that satisfy certain criteria while fitting the regression models. The bounds involve drawing values from a truncated predictive distribution. The development of this method was partly motivated by the analysis of two data sets which are used as illustrations. The sequential regression procedure is applied to perform multiple imputation analysis for the two applied problems. The sampling properties of inferences from multiply imputed data sets created using the sequential regression method are evaluated through simulated data sets.
Release date: 2001-08-22 - Articles and reports: 12-001-X20010015858Description:
The objective of this paper is to study and measure the change (from the initial to the final weight) which results from the procedure used to modify weights. A breakdown of the final weights is proposed in order to evaluate the relative impact of the nonresponse adjustment, the correction for poststratification and the interaction between these two adjustments. This measure of change is used as a tool for comparing the effectiveness of the various methods for adjusting for nonresponse, in particular the methods relying on the formation of Response Homogeneity Groups. The measure of change is examined through a simulation study, which uses data from a Statistics Canada longitudinal survey, the Survey of Labour and Income Dynamics. The measure of change is also applied to data obtained from a second longitudinal survey, the National Longitudinal Survey of Children and Youth.
Release date: 2001-08-22 - Articles and reports: 12-001-X20010015859Description:
In 2001, the INSEE conducted a survey to better understand the homeless population. Since there was no survey frame to allow direct access to homeless persons, the survey principle involved sampling the services they received and questioning the individuals who used those services. Weighting the individual input to the survey proved difficult because a single individual could receive several services within the designated reference period. This article shows how it is possible to apply the weight sharing method to resolve this problem. In this type of survey, a single variable can produce several parameters of interest corresponding to populations varying with time. A set of weights corresponds to each definition of parameters. The article focuses, in particular, on "an average day" and "an average week" weight calculation. Information is also provided on the use data to be collected and the nonresponse adjustment.
Release date: 2001-08-22
Reference (17)
Reference (17) (0 to 10 of 17 results)
- 1. User Guide - Survey of Household Spending, 2000 ArchivedSurveys and statistical programs – Documentation: 62F0026M2001004Geography: Province or territoryDescription:
This guide presents information of interest to users of data from the Survey of Household Spending. Data are collected via personal interview conducted in January, February and March after the reference year using a paper questionnaire. Information is gathered about the spending habits, dwelling characteristics and household equipment of Canadian households during the reference year. The survey covers private households in the ten provinces. (The three territories are surveyed every second year starting in 2001.)
This guide includes definitions of survey terms and variables, as well as descriptions of survey methodology and data quality. There is also a section describing the various statistics that can be created using expenditure data (e.g., budget share, market share, and aggregates).
Release date: 2001-12-12 - Surveys and statistical programs – Documentation: 62F0026M2001001Description:
This report describes the quality indicators produced for the 1998 Survey of Household Spending. It covers the usual quality indicators that help users interpret data, such as coefficients of variation, nonresponse rates, imputation rates and the impact of imputed data on the estimates. Added to these are various less often used indicators such as slippage rates and measures of the representativity of the sample for particular characteristics that are useful for evaluating the survey methodology.
Release date: 2001-10-15 - Surveys and statistical programs – Documentation: 62F0026M2001002Description:
This report describes the quality indicators produced for the 1999 Survey of Household Spending. It covers the usual quality indicators that help users interpret data, such as coefficients of variation, nonresponse rates, imputation rates and the impact of imputed data on the estimates. Added to these are various less often used indicators such as slippage rates and measures of the representativity of the sample for particular characteristics that are useful for evaluating the survey methodology.
Release date: 2001-10-15 - 4. Methodology of the Survey of Household Spending ArchivedSurveys and statistical programs – Documentation: 62F0026M2001003Description:
This document provides a detailed description of the methodology of the Survey of Household Spending. Topics covered include: target population; sample design; data collection; data processing; weighting and estimation; estimation of sampling error; and data suppression and confidentiality.
Release date: 2001-10-15 - 5. Survey of Financial Security - Methodology for Estimating the Value of Employer Pension Plan Benefits ArchivedSurveys and statistical programs – Documentation: 13F0026M2001003Description:
Initial results from the Survey of Financial Security (SFS), which provides information on the net worth of Canadians, were released on March 15 2001, in The daily. The survey collected information on the value of the financial and non-financial assets owned by each family unit and on the amount of their debt.
Statistics Canada is currently refining this initial estimate of net worth by adding to it an estimate of the value of benefits accrued in employer pension plans. This is an important addition to any asset and debt survey as, for many family units, it is likely to be one of the largest assets. With the aging of the population, information on pension accumulations is greatly needed to better understand the financial situation of those nearing retirement. These updated estimates of the Survey of Financial Security will be released in late fall 2001.
The process for estimating the value of employer pension plan benefits is a complex one. This document describes the methodology for estimating that value, for the following groups: a) persons who belonged to an RPP at the time of the survey (referred to as current plan members); b) persons who had previously belonged to an RPP and either left the money in the plan or transferred it to a new plan; c) persons who are receiving RPP benefits.
This methodology was proposed by Hubert Frenken and Michael Cohen. The former has many years of experience with Statistics Canada working with data on employer pension plans; the latter is a principal with the actuarial consulting firm William M. Mercer. Earlier this year, Statistics Canada carried out a public consultation on the proposed methodology. This report includes updates made as a result of feedback received from data users.
Release date: 2001-09-05 - Surveys and statistical programs – Documentation: 71F0031X2000001Description:
This paper introduces and explains modifications made to the Labour Force Survey estimates in January 2000. Some of these modifications include the adjustment of all LFS estimates to reflect population counts based on the 1996 Census plus the implementation of a new estimation methodology called composite estimation. This new method results in more efficient estimates of month to month change, while improving the quality of monthly level estimates.
Release date: 2001-06-29 - Surveys and statistical programs – Documentation: 13-604-M2002037Description:
A new accounting approach treats software as an investment was implemented in the Canadian System of National Accounts (SNA) during 2001. Preliminary estimates of software capital stocks were included for the first time in the National Balance Sheet Accounts (NBSA) released in March 2001. Software investment was then included in the gross domestic product (GDP) with the first quarter 2001 release (May 31, 2001) of the National Economic and Financial Accounts (NEFA). Later in the year, it was included in the Input-Output (I/O) Accounts, Provincial Economic Accounts (PEA) and the Industry Measures Accounts (IMA) with the release of October 30, 2001.
This mini historical revision brings Canada in line with a number of countries, including the United States and other G-7 member nations, who introduced software into their GDP over the last few years. It also brings Canada in line with the 1993 SNA recommendation that business and government acquisition of software be treated in national accounts as an investment as opposed to a current expense. Software is now treated like any other capital input that is used repeatedly in production over a year or more whereas, formerly, it was treated as if it were fully used up during the production period like any other intermediate input. This new accounting for software has raised the level of GDP, although the effects on GDP growth turn out to be relatively small.
Release date: 2001-05-31 - 8. Entry Exit Component for Labour Interview: January 2000, Survey of Labour and Income Dynamics ArchivedSurveys and statistical programs – Documentation: 75F0002M2000013Description:
This document presents the information for the new entry exit portion of the Survey of Labour and Income Dynamics (SLID) labour interview.
Release date: 2001-04-17 - Surveys and statistical programs – Documentation: 75F0002M2000015Description:
This document outlines the structure of the January 2000 Survey of Labour and Income Dynamics (SLID) labour interview, including question wording, possible responses, and flows of questions.
Release date: 2001-04-17 - 10. Entry Exit Component for Income Interview: May 2000, Survey of Labour and Income Dynamics ArchivedSurveys and statistical programs – Documentation: 75F0002M2000012Description:
This document presents the information for the new entry exit portion of the Survey of Labour and Income Dynamics (SLID) income interview.
Release date: 2001-03-27
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