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- Articles and reports: 12-001-X201500114151Description:
One of the main variables in the Dutch Labour Force Survey is the variable measuring whether a respondent has a permanent or a temporary job. The aim of our study is to determine the measurement error in this variable by matching the information obtained by the longitudinal part of this survey with unique register data from the Dutch Institute for Employee Insurance. Contrary to previous approaches confronting such datasets, we take into account that also register data are not error-free and that measurement error in these data is likely to be correlated over time. More specifically, we propose the estimation of the measurement error in these two sources using an extended hidden Markov model with two observed indicators for the type of contract. Our results indicate that none of the two sources should be considered as error-free. For both indicators, we find that workers in temporary contracts are often misclassified as having a permanent contract. Particularly for the register data, we find that measurement errors are strongly autocorrelated, as, if made, they tend to repeat themselves. In contrast, when the register is correct, the probability of an error at the next time period is almost zero. Finally, we find that temporary contracts are more widespread than the Labour Force Survey suggests, while transition rates between temporary to permanent contracts are much less common than both datasets suggest.
Release date: 2015-06-29 - Articles and reports: 12-001-X201200111684Description:
Many business surveys provide estimates for the monthly turnover for the major Standard Industrial Classification codes. This includes estimates for the change in the level of the monthly turnover compared to 12 months ago. Because business surveys often use overlapping samples, the turnover estimates in consecutive months are correlated. This makes the variance calculations for a change less straightforward. This article describes a general variance estimation procedure. The procedure allows for yearly stratum corrections when establishments move into other strata according to their actual sizes. The procedure also takes into account sample refreshments, births and deaths. The paper concludes with an example of the variance for the estimated yearly growth rate of the monthly turnover of Dutch Supermarkets.
Release date: 2012-06-27 - Articles and reports: 12-001-X200900211040Description:
In this paper a multivariate structural time series model is described that accounts for the panel design of the Dutch Labour Force Survey and is applied to estimate monthly unemployment rates. Compared to the generalized regression estimator, this approach results in a substantial increase of the accuracy due to a reduction of the standard error and the explicit modelling of the bias between the subsequent waves.
Release date: 2009-12-23 - 4. An integrated modeling approach to unemployment rate estimation for sub-provincial areas of Canada ArchivedArticles and reports: 12-001-X200800110614Geography: CanadaDescription:
The Canadian Labour Force Survey (LFS) produces monthly estimates of the unemployment rate at national and provincial levels. The LFS also releases unemployment estimates for sub-provincial areas such as Census Metropolitan Areas (CMAs) and Urban Centers (UCs). However, for some sub-provincial areas, the direct estimates are not reliable since the sample size in some areas is quite small. The small area estimation in LFS concerns estimation of unemployment rates for local sub-provincial areas such as CMA/UCs using small area models. In this paper, we will discuss various models including the Fay-Herriot model and cross-sectional and time series models. In particular, an integrated non-linear mixed effects model will be proposed under the hierarchical Bayes (HB) framework for the LFS unemployment rate estimation. Monthly Employment Insurance (EI) beneficiary data at the CMA/UC level are used as auxiliary covariates in the model. A HB approach with the Gibbs sampling method is used to obtain the estimates of posterior means and posterior variances of the CMA/UC level unemployment rates. The proposed HB model leads to reliable model-based estimates in terms of CV reduction. Model fit analysis and comparison of the model-based estimates with the direct estimates are presented in the paper.
Release date: 2008-06-26 - Articles and reports: 12-001-X20060019258Description:
This paper primarily aims at proposing a cost-effective strategy to estimate the intercensal unemployment rate at the provincial level in Iran. Taking advantage of the small area estimation (SAE) methods, this strategy is based on a single sampling at the national level. Three methods of synthetic, composite, and empirical Bayes estimators are used to find the indirect estimates of interest for the year 1996. Findings not only confirm the adequacy of the suggested strategy, but they also indicate that the composite and empirical Bayes estimators perform well and similarly.
Release date: 2006-07-20 - Articles and reports: 12-001-X20040016998Description:
The Canadian Labour Force Survey (LFS) was not designed to be a longitudinal survey. However, given that respondent households typically remain in the sample for six consecutive months, it is possible to reconstruct six-month fragments of longitudinal data from the monthly records of household members. Such longitudinal micro-data - altogether consisting of millions of person-months of individual and family level data - is useful for analyses of monthly labour market dynamics over relatively long periods of time, 25 years and more.
We make use of these data to estimate hazard functions describing transitions among the labour market states: self-employed, paid employee and not employed. Data on job tenure, for employed respondents, and on the date last worked, for those not employed - together with the date of survey responses - allow the construction of models that include terms reflecting seasonality and macro-economic cycles as well as the duration dependence of each type of transition. In addition, the LFS data permits spouse labour market activity and family composition variables to be included in the hazard models as time-varying covariates. The estimated hazard equations have been incorporated in the LifePaths microsimulation model. In that setting, the equations have been used to simulate lifetime employment activity from past, present and future birth cohorts. Simulation results have been validated by comparison with the age profiles of LFS employment/population ratios for the period 1976 to 2001.
Release date: 2004-07-14 - 7. Model-based unemployment rate estimation for the Canadian Labour Force Survey: A hierarchical Bayes approach ArchivedArticles and reports: 12-001-X20030016602Description:
The Canadian Labour Force Survey (LFS) produces monthly direct estimates of the unemployment rate at national and provincial levels. The LFS also releases unemployment estimates for subprovincial areas such as census metropolitan areas (CMAs) and census agglomerations (CAs). However, for some subprovincial areas, the direct estimates are not very reliable since the sample size in some areas is quite small. In this paper, a cross-sectional and time-series model is used to borrow strength across areas and time periods to produce model-based unemployment rate estimates for CMAs and CAs. This model is a generalization of a widely used cross-sectional model in small area estimation and includes a random walk or AR(1) model for the random time component. Monthly Employment Insurance (EI) beneficiary data at the CMA or CA level are used as auxiliary covariates in the model. A hierarchical Bayes (HB) approach is employed and the Gibbs sampler is used to generate samples from the joint posterior distribution. Rao-Blackwellized estimators are obtained for the posterior means and posterior variances of the CMA/CA-level unemployment rates. The HB method smoothes the survey estimates and leads to a substantial reduction in standard errors. Base on posterior distributions, bayesian model fitting is also investigated in this paper.
Release date: 2003-07-31 - Articles and reports: 12-001-X20030016607Description:
The Korean Economically Active Population Survey (EAPS) has been conducted in order to produce unemployment statistics for large areas such as metropolitan cities and provincial levels. Large areas have been designated as planned domains in the EAPS and local self-government areas (LSGAs) as unplanned domains. In this study, we suggest small area estimation methods to adjust for the unemployment statistics of LSGAs within large areas estimated directly from current EAPS data. We suggest synthetic and composite estimators under the Korean EAPS system, and for the model-based estimator we put forward the hierarchical Bayes (HB) estimator from the general multi-level model. The HB estimator we use here was introduced by You and Rao (2000). The mean square errors of the synthetic and composite estimates are derived from the EAPS data by the Jackknife method, and are used as a measure of accuracy for the small area estimates. Gibbs sampling is used to obtain the HB estimates and their posterior variances, which we use to measure precision for small area estimates. The total unemployment figures of the 10 LSGAs within the ChoongBuk Province produced by the December 2000 EAPS data have been estimated using the small area estimation methods suggested in this study. The reliability of small area estimates is evaluated by the relative standard errors or the relative root mean square errors of these estimates. Here, under the current Korean EAPS system, we suggest that the composite estimates are more reliable than other small area estimates.
Release date: 2003-07-31 - Articles and reports: 12-001-X20030016613Description:
The Illinois Department of Employment Security is using small domain estimation techniques to estimate employment at the county or industry divisional level. The estimator is a standard synthetic estimator, based on the ability to match Current Employment Statistics sample data to ES202 administrative records and an assumed model relationship between the two data sources. This paper is a case study that reviews the steps taken to evaluate the appropriateness of the model and the difficulties encountered in linking the two data sources.
Release date: 2003-07-31 - Articles and reports: 12-001-X20020016421Description:
Like most other surveys, non-response often occurs in the Current Employment Survey conducted monthly by the U.S. Bureau of Labor Statistics (BLS). In a given month, imputation using reported data from previous months generally provides more efficient survey estimators than ignoring non-respondents and adjusting survey weights. However, imputation also has an effect on variance estimation: treating imputed values as reported data and applying a standard variance estimation method lead to negatively biased variance estimators. In this article, we propose some variance estimators using the Grouped Balanced Half Sample method and re-imputation to take imputation into account. Some simulation results for the finite sample performance of the imputed survey estimators and their variance estimators are presented.
Release date: 2002-07-05
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Articles and reports (16)
Articles and reports (16) (0 to 10 of 16 results)
- Articles and reports: 12-001-X201500114151Description:
One of the main variables in the Dutch Labour Force Survey is the variable measuring whether a respondent has a permanent or a temporary job. The aim of our study is to determine the measurement error in this variable by matching the information obtained by the longitudinal part of this survey with unique register data from the Dutch Institute for Employee Insurance. Contrary to previous approaches confronting such datasets, we take into account that also register data are not error-free and that measurement error in these data is likely to be correlated over time. More specifically, we propose the estimation of the measurement error in these two sources using an extended hidden Markov model with two observed indicators for the type of contract. Our results indicate that none of the two sources should be considered as error-free. For both indicators, we find that workers in temporary contracts are often misclassified as having a permanent contract. Particularly for the register data, we find that measurement errors are strongly autocorrelated, as, if made, they tend to repeat themselves. In contrast, when the register is correct, the probability of an error at the next time period is almost zero. Finally, we find that temporary contracts are more widespread than the Labour Force Survey suggests, while transition rates between temporary to permanent contracts are much less common than both datasets suggest.
Release date: 2015-06-29 - Articles and reports: 12-001-X201200111684Description:
Many business surveys provide estimates for the monthly turnover for the major Standard Industrial Classification codes. This includes estimates for the change in the level of the monthly turnover compared to 12 months ago. Because business surveys often use overlapping samples, the turnover estimates in consecutive months are correlated. This makes the variance calculations for a change less straightforward. This article describes a general variance estimation procedure. The procedure allows for yearly stratum corrections when establishments move into other strata according to their actual sizes. The procedure also takes into account sample refreshments, births and deaths. The paper concludes with an example of the variance for the estimated yearly growth rate of the monthly turnover of Dutch Supermarkets.
Release date: 2012-06-27 - Articles and reports: 12-001-X200900211040Description:
In this paper a multivariate structural time series model is described that accounts for the panel design of the Dutch Labour Force Survey and is applied to estimate monthly unemployment rates. Compared to the generalized regression estimator, this approach results in a substantial increase of the accuracy due to a reduction of the standard error and the explicit modelling of the bias between the subsequent waves.
Release date: 2009-12-23 - 4. An integrated modeling approach to unemployment rate estimation for sub-provincial areas of Canada ArchivedArticles and reports: 12-001-X200800110614Geography: CanadaDescription:
The Canadian Labour Force Survey (LFS) produces monthly estimates of the unemployment rate at national and provincial levels. The LFS also releases unemployment estimates for sub-provincial areas such as Census Metropolitan Areas (CMAs) and Urban Centers (UCs). However, for some sub-provincial areas, the direct estimates are not reliable since the sample size in some areas is quite small. The small area estimation in LFS concerns estimation of unemployment rates for local sub-provincial areas such as CMA/UCs using small area models. In this paper, we will discuss various models including the Fay-Herriot model and cross-sectional and time series models. In particular, an integrated non-linear mixed effects model will be proposed under the hierarchical Bayes (HB) framework for the LFS unemployment rate estimation. Monthly Employment Insurance (EI) beneficiary data at the CMA/UC level are used as auxiliary covariates in the model. A HB approach with the Gibbs sampling method is used to obtain the estimates of posterior means and posterior variances of the CMA/UC level unemployment rates. The proposed HB model leads to reliable model-based estimates in terms of CV reduction. Model fit analysis and comparison of the model-based estimates with the direct estimates are presented in the paper.
Release date: 2008-06-26 - Articles and reports: 12-001-X20060019258Description:
This paper primarily aims at proposing a cost-effective strategy to estimate the intercensal unemployment rate at the provincial level in Iran. Taking advantage of the small area estimation (SAE) methods, this strategy is based on a single sampling at the national level. Three methods of synthetic, composite, and empirical Bayes estimators are used to find the indirect estimates of interest for the year 1996. Findings not only confirm the adequacy of the suggested strategy, but they also indicate that the composite and empirical Bayes estimators perform well and similarly.
Release date: 2006-07-20 - Articles and reports: 12-001-X20040016998Description:
The Canadian Labour Force Survey (LFS) was not designed to be a longitudinal survey. However, given that respondent households typically remain in the sample for six consecutive months, it is possible to reconstruct six-month fragments of longitudinal data from the monthly records of household members. Such longitudinal micro-data - altogether consisting of millions of person-months of individual and family level data - is useful for analyses of monthly labour market dynamics over relatively long periods of time, 25 years and more.
We make use of these data to estimate hazard functions describing transitions among the labour market states: self-employed, paid employee and not employed. Data on job tenure, for employed respondents, and on the date last worked, for those not employed - together with the date of survey responses - allow the construction of models that include terms reflecting seasonality and macro-economic cycles as well as the duration dependence of each type of transition. In addition, the LFS data permits spouse labour market activity and family composition variables to be included in the hazard models as time-varying covariates. The estimated hazard equations have been incorporated in the LifePaths microsimulation model. In that setting, the equations have been used to simulate lifetime employment activity from past, present and future birth cohorts. Simulation results have been validated by comparison with the age profiles of LFS employment/population ratios for the period 1976 to 2001.
Release date: 2004-07-14 - 7. Model-based unemployment rate estimation for the Canadian Labour Force Survey: A hierarchical Bayes approach ArchivedArticles and reports: 12-001-X20030016602Description:
The Canadian Labour Force Survey (LFS) produces monthly direct estimates of the unemployment rate at national and provincial levels. The LFS also releases unemployment estimates for subprovincial areas such as census metropolitan areas (CMAs) and census agglomerations (CAs). However, for some subprovincial areas, the direct estimates are not very reliable since the sample size in some areas is quite small. In this paper, a cross-sectional and time-series model is used to borrow strength across areas and time periods to produce model-based unemployment rate estimates for CMAs and CAs. This model is a generalization of a widely used cross-sectional model in small area estimation and includes a random walk or AR(1) model for the random time component. Monthly Employment Insurance (EI) beneficiary data at the CMA or CA level are used as auxiliary covariates in the model. A hierarchical Bayes (HB) approach is employed and the Gibbs sampler is used to generate samples from the joint posterior distribution. Rao-Blackwellized estimators are obtained for the posterior means and posterior variances of the CMA/CA-level unemployment rates. The HB method smoothes the survey estimates and leads to a substantial reduction in standard errors. Base on posterior distributions, bayesian model fitting is also investigated in this paper.
Release date: 2003-07-31 - Articles and reports: 12-001-X20030016607Description:
The Korean Economically Active Population Survey (EAPS) has been conducted in order to produce unemployment statistics for large areas such as metropolitan cities and provincial levels. Large areas have been designated as planned domains in the EAPS and local self-government areas (LSGAs) as unplanned domains. In this study, we suggest small area estimation methods to adjust for the unemployment statistics of LSGAs within large areas estimated directly from current EAPS data. We suggest synthetic and composite estimators under the Korean EAPS system, and for the model-based estimator we put forward the hierarchical Bayes (HB) estimator from the general multi-level model. The HB estimator we use here was introduced by You and Rao (2000). The mean square errors of the synthetic and composite estimates are derived from the EAPS data by the Jackknife method, and are used as a measure of accuracy for the small area estimates. Gibbs sampling is used to obtain the HB estimates and their posterior variances, which we use to measure precision for small area estimates. The total unemployment figures of the 10 LSGAs within the ChoongBuk Province produced by the December 2000 EAPS data have been estimated using the small area estimation methods suggested in this study. The reliability of small area estimates is evaluated by the relative standard errors or the relative root mean square errors of these estimates. Here, under the current Korean EAPS system, we suggest that the composite estimates are more reliable than other small area estimates.
Release date: 2003-07-31 - Articles and reports: 12-001-X20030016613Description:
The Illinois Department of Employment Security is using small domain estimation techniques to estimate employment at the county or industry divisional level. The estimator is a standard synthetic estimator, based on the ability to match Current Employment Statistics sample data to ES202 administrative records and an assumed model relationship between the two data sources. This paper is a case study that reviews the steps taken to evaluate the appropriateness of the model and the difficulties encountered in linking the two data sources.
Release date: 2003-07-31 - Articles and reports: 12-001-X20020016421Description:
Like most other surveys, non-response often occurs in the Current Employment Survey conducted monthly by the U.S. Bureau of Labor Statistics (BLS). In a given month, imputation using reported data from previous months generally provides more efficient survey estimators than ignoring non-respondents and adjusting survey weights. However, imputation also has an effect on variance estimation: treating imputed values as reported data and applying a standard variance estimation method lead to negatively biased variance estimators. In this article, we propose some variance estimators using the Grouped Balanced Half Sample method and re-imputation to take imputation into account. Some simulation results for the finite sample performance of the imputed survey estimators and their variance estimators are presented.
Release date: 2002-07-05
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