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All (28) (20 to 30 of 28 results)
- Articles and reports: 75F0002M1993018Description:
This paper evaluates alternatives for weighting persons who join households after a respondent panel has been selected.
Release date: 1995-12-30 - Articles and reports: 11F0019M1995081Geography: CanadaDescription:
Users of socio-economic statistics typically want more and better information. Often, these needs can be met simply by more extensive data collections, subject to usual concerns over financial costs and survey respondent burdens. Users, particularly for public policy purposes, have also expressed a continuing, and as yet unfilled, demand for an integrated and coherent system of socio-economic statistics. In this case, additional data will not be sufficient; the more important constraint is the absence of an agreed conceptual approach.
In this paper, we briefly review the state of frameworks for social and economic statistics, including the kinds of socio-economic indicators users may want. These indicators are motivated first in general terms from basic principles and intuitive concepts, leaving aside for the moment the practicalities of their construction. We then show how a coherent structure of such indicators might be assembled.
A key implication is that this structure requires a coordinated network of surveys and data collection processes, and higher data quality standards. This in turn implies a breaking down of the "stovepipe" systems that typify much of the survey work in national statistical agencies (i.e. parallel but generally unrelated data "production lines"). Moreover, the data flowing from the network of surveys must be integrated. Since the data of interest are dynamic, the proposed method goes beyond statistical matching to microsimulation modeling. Finally, these ideas are illustrated with preliminary results from the LifePaths model currently under development in Statistics Canada.
Release date: 1995-07-30 - Articles and reports: 11F0019M1995067Geography: CanadaDescription:
The role of technical innovation in economic growth is both a current matter of keen public policy interest, and active exploration in economic theory. However, formal economic theorizing is often constrained by considerations of mathematical tractability. Evolutionary economic theories which are realized as computerized microsimulation models offer significant promise both for transcending mathematical constraints and addressing fundamental questions in a more realistic and flexible manner. This paper sketches XEcon, a microsimulation model of economic growth in the evolutionary tradition.
Release date: 1995-06-30 - 24. Empirical comparison of small area estimation methods for the Italian Labour Force Survey ArchivedArticles and reports: 12-001-X199400214419Description:
The study was undertaken to evaluate some alternative small areas estimators to produce level estimates for unplanned domains from the Italian Labour Force Sample Survey. In our study, the small areas are the Health Service Areas, which are unplanned sub-regional territorial domains and were not isolated at the time of sample design and thus cut across boundaries of the design strata. We consider the following estimators: post-stratified ratio, synthetic, composite expressed as linear combination of synthetic and of post-stratified ratio, and sample size dependent. For all the estimators considered in this study, the average percent relative biases and the average relative mean square errors were obtained in a Monte Carlo study in which the sample design was simulated using data from the 1981 Italian Census.
Release date: 1994-12-15 - 25. Bias corrections for survey estimates from data with ratio imputed values for confounded nonresponse ArchivedArticles and reports: 12-001-X199400214423Description:
Most surveys suffer from the problem of missing data caused by nonresponse. To deal with this problem, imputation is often used to create a “completed data set”, that is, a data set composed of actual observations (for the respondents) and imputations (for the nonrespondents). Usually, imputation is carried out under the assumption of unconfounded response mechanism. When this assumption does not hold, a bias is introduced in the standard estimator of the population mean calculated from the completed data set. In this paper, we pursue the idea of using simple correction factors for the bias problem in the case that ratio imputation is used. The effectiveness of the correction factors is studied by Monte Carlo simulation using artificially generated data sets representing various super-populations, nonresponse rates, nonresponse mechanisms, and correlations between the variable of interest and the auxiliary variable. These correction factors are found to be effective especially when the population follows the model underlying ratio imputation. An option for estimating the variance of the corrected point estimates is also discussed.
Release date: 1994-12-15 - 26. Statistical matching: Use of auxiliary information as an alternative to the conditional independence assumption ArchivedArticles and reports: 12-001-X199300114475Description:
In the creation of micro-simulation databases which are frequently used by policy analysts and planners, several datafiles are combined by statistical matching techniques for enriching the host datafile. This process requires the conditional independence assumption (CIA) which could lead to serious bias in the resulting joint relationships among variables. Appropriate auxiliary information could be used to avoid the CIA. In this report, methods of statistical matching corresponding to three methods of imputation, namely, regression, hot deck, and log linear, with and without auxiliary information are considered. The log linear methods consist of adding categorical constraints to either the regression or hot deck methods. Based on an extensive simulation study with synthetic data, sensitivity analyses for departures from the CIA are performed and gains from using auxiliary information are discussed. Different scenarios for the underlying distribution and relationships, such as symmetric versus skewed data and proxy versus nonproxy auxiliary data, are created using synthetic data. Some recommendations on the use of statistical matching methods are also made. Specifically, it was confirmed that the CIA could be a serious limitation which could be overcome by the use of appropriate auxiliary information. Hot deck methods were found to be generally preferable to regression methods. Also, when auxiliary information is available, log linear categorical constraints can improve performance of hot deck methods. This study was motivated by concerns about the use of the CIA in the construction of the Social Policy Simulation Database at Statistics Canada.
Release date: 1993-06-15 - 27. County estimates of wheat production ArchivedArticles and reports: 12-001-X199100214501Description:
Although farm surveys carried out by the USDA are used to estimate crop production at the state and national levels, small area estimates at the county level are more useful for local economic decision making. County estimates are also in demand by companies selling fertilizers, pesticides, crop insurance, and farm equipment. Individual states often conduct their own surveys to provide data for county estimates of farm production. Typically, these state surveys are not carried out using probability sampling methods. An additional complication is that states impose the constraint that the sum of county estimates of crop production for all counties in a state be equal to the USDA estimate for that state. Thus, standard small area estimation procedures are not directly applicable to this problem. In this paper, we consider using regression models for obtaining county estimates of wheat production in Kansas. We describe a simulation study comparing the resulting estimates to those obtained using two standard small area estimators: the synthetic and direct estimators. We also compare several strategies for scaling the initial estimates so that they agree with the USDA estimate of the state production total.
Release date: 1991-12-16 - Articles and reports: 12-001-X197800254834Description: Frames designed for continuous surveys are sometimes used for ad hoc surveys which require selection of sampling units separate from those selected for the continuous survey. This paper presents an unbiased extension of Keyfitz’s (1951) sample updating method to the case where a portion of the frame has been reserved for surveys other than the main continuous survey. A simple although biased alternative is presented. The scope under Platek and Singh’s (1975) design strategy for an area based continuous survey requiring updating is then expanded to encompass rotation of first stage units, establishment of a separate special survey sub-frame, and procedures to prevent re-selection of ultimate sampling units. The methods are evaluated in a Monte Carlo study using Census data to simulate the design for the Canadian Labour Force Survey.Release date: 1978-12-15
Data (2)
Data (2) ((2 results))
- Table: 89-26-0006Description: PASSAGES is an open-source dynamic microsimulation model aimed at supporting policy analysis and research relating to Canadian retirement income system outcomes at the individual and family level. The publicly available version includes a synthetic starting database, a model, and documentation. A confidential starting database is also available.Release date: 2024-04-23
- Public use microdata: 89F0002XDescription: The SPSD/M is a static microsimulation model designed to analyse financial interactions between governments and individuals in Canada. It can compute taxes paid to and cash transfers received from government. It is comprised of a database, a series of tax/transfer algorithms and models, analytical software and user documentation.Release date: 2024-04-12
Analysis (25)
Analysis (25) (20 to 30 of 25 results)
- 21. Empirical comparison of small area estimation methods for the Italian Labour Force Survey ArchivedArticles and reports: 12-001-X199400214419Description:
The study was undertaken to evaluate some alternative small areas estimators to produce level estimates for unplanned domains from the Italian Labour Force Sample Survey. In our study, the small areas are the Health Service Areas, which are unplanned sub-regional territorial domains and were not isolated at the time of sample design and thus cut across boundaries of the design strata. We consider the following estimators: post-stratified ratio, synthetic, composite expressed as linear combination of synthetic and of post-stratified ratio, and sample size dependent. For all the estimators considered in this study, the average percent relative biases and the average relative mean square errors were obtained in a Monte Carlo study in which the sample design was simulated using data from the 1981 Italian Census.
Release date: 1994-12-15 - 22. Bias corrections for survey estimates from data with ratio imputed values for confounded nonresponse ArchivedArticles and reports: 12-001-X199400214423Description:
Most surveys suffer from the problem of missing data caused by nonresponse. To deal with this problem, imputation is often used to create a “completed data set”, that is, a data set composed of actual observations (for the respondents) and imputations (for the nonrespondents). Usually, imputation is carried out under the assumption of unconfounded response mechanism. When this assumption does not hold, a bias is introduced in the standard estimator of the population mean calculated from the completed data set. In this paper, we pursue the idea of using simple correction factors for the bias problem in the case that ratio imputation is used. The effectiveness of the correction factors is studied by Monte Carlo simulation using artificially generated data sets representing various super-populations, nonresponse rates, nonresponse mechanisms, and correlations between the variable of interest and the auxiliary variable. These correction factors are found to be effective especially when the population follows the model underlying ratio imputation. An option for estimating the variance of the corrected point estimates is also discussed.
Release date: 1994-12-15 - 23. Statistical matching: Use of auxiliary information as an alternative to the conditional independence assumption ArchivedArticles and reports: 12-001-X199300114475Description:
In the creation of micro-simulation databases which are frequently used by policy analysts and planners, several datafiles are combined by statistical matching techniques for enriching the host datafile. This process requires the conditional independence assumption (CIA) which could lead to serious bias in the resulting joint relationships among variables. Appropriate auxiliary information could be used to avoid the CIA. In this report, methods of statistical matching corresponding to three methods of imputation, namely, regression, hot deck, and log linear, with and without auxiliary information are considered. The log linear methods consist of adding categorical constraints to either the regression or hot deck methods. Based on an extensive simulation study with synthetic data, sensitivity analyses for departures from the CIA are performed and gains from using auxiliary information are discussed. Different scenarios for the underlying distribution and relationships, such as symmetric versus skewed data and proxy versus nonproxy auxiliary data, are created using synthetic data. Some recommendations on the use of statistical matching methods are also made. Specifically, it was confirmed that the CIA could be a serious limitation which could be overcome by the use of appropriate auxiliary information. Hot deck methods were found to be generally preferable to regression methods. Also, when auxiliary information is available, log linear categorical constraints can improve performance of hot deck methods. This study was motivated by concerns about the use of the CIA in the construction of the Social Policy Simulation Database at Statistics Canada.
Release date: 1993-06-15 - 24. County estimates of wheat production ArchivedArticles and reports: 12-001-X199100214501Description:
Although farm surveys carried out by the USDA are used to estimate crop production at the state and national levels, small area estimates at the county level are more useful for local economic decision making. County estimates are also in demand by companies selling fertilizers, pesticides, crop insurance, and farm equipment. Individual states often conduct their own surveys to provide data for county estimates of farm production. Typically, these state surveys are not carried out using probability sampling methods. An additional complication is that states impose the constraint that the sum of county estimates of crop production for all counties in a state be equal to the USDA estimate for that state. Thus, standard small area estimation procedures are not directly applicable to this problem. In this paper, we consider using regression models for obtaining county estimates of wheat production in Kansas. We describe a simulation study comparing the resulting estimates to those obtained using two standard small area estimators: the synthetic and direct estimators. We also compare several strategies for scaling the initial estimates so that they agree with the USDA estimate of the state production total.
Release date: 1991-12-16 - Articles and reports: 12-001-X197800254834Description: Frames designed for continuous surveys are sometimes used for ad hoc surveys which require selection of sampling units separate from those selected for the continuous survey. This paper presents an unbiased extension of Keyfitz’s (1951) sample updating method to the case where a portion of the frame has been reserved for surveys other than the main continuous survey. A simple although biased alternative is presented. The scope under Platek and Singh’s (1975) design strategy for an area based continuous survey requiring updating is then expanded to encompass rotation of first stage units, establishment of a separate special survey sub-frame, and procedures to prevent re-selection of ultimate sampling units. The methods are evaluated in a Monte Carlo study using Census data to simulate the design for the Canadian Labour Force Survey.Release date: 1978-12-15
Reference (1)
Reference (1) ((1 result))
- Surveys and statistical programs – Documentation: 11-522-X201300014290Description:
This paper describes a new module that will project families and households by Aboriginal status using the Demosim microsimulation model. The methodology being considered would assign a household/family headship status annually to each individual and would use the headship rate method to calculate the number of annual families and households by various characteristics and geographies associated with Aboriginal populations.
Release date: 2014-10-31
- Date modified: