Analysis

All (2) ((2 results))

• 1. Small area estimation of the number of firms' recruits by using multivariate models for count data Archived

  Articles and reports: 12-001-X201000211379

  Description:

  The number of people recruited by firms in Local Labour Market Areas provides an important indicator of the reorganisation of the local productive processes. In Italy, this parameter can be estimated using the information collected in the Excelsior survey, although it does not provide reliable estimates for the domains of interest. In this paper we propose a multivariate small area estimation approach for count data based on the Multivariate Poisson-Log Normal distribution. This approach will be used to estimate the number of firm recruits both replacing departing employees and filling new positions. In the small area estimation framework, it is customary to assume that sampling variances and covariances are known. However, both they and the direct point estimates suffer from instability. Due to the rare nature of the phenomenon we are analysing, counts in some domains are equal to zero, and this produces estimates of sampling error covariances equal to zero. To account for the extra variability due to the estimated sampling covariance matrix, and to deal with the problem of unreasonable estimated variances and covariances in some domains, we propose an "integrated" approach where we jointly model the parameters of interest and the sampling error covariance matrices. We suggest a solution based again on the Poisson-Log Normal distribution to smooth variances and covariances. The results we obtain are encouraging: the proposed small area estimation model shows a better fit when compared to the Multivariate Normal-Normal (MNN) small area model, and it allows for a non-negligible increase in efficiency.

  Release date: 2010-12-21

  ---

• 2. Small area estimation of average household income based on unit level models for panel data Archived

  Articles and reports: 12-001-X200700210496

  Description:

  The European Community Household Panel (ECHP) is a panel survey covering a wide range of topics regarding economic, social and living conditions. In particular, it makes it possible to calculate disposable equivalized household income, which is a key variable in the study of economic inequity and poverty. To obtain reliable estimates of the average of this variable for regions within countries it is necessary to have recourse to small area estimation methods. In this paper, we focus on empirical best linear predictors of the average equivalized income based on "unit level models" borrowing strength across both areas and times. Using a simulation study based on ECHP data, we compare the suggested estimators with cross-sectional model-based and design-based estimators. In the case of these empirical predictors, we also compare three different MSE estimators. Results show that those estimators connected to models that take units' autocorrelation into account lead to a significant gain in efficiency, even when there are no covariates available whose population mean is known.

  Release date: 2008-01-03

Stats in brief (0) (0 results)

No content available at this time.

Articles and reports (2) ((2 results))

• 1. Small area estimation of the number of firms' recruits by using multivariate models for count data Archived

  Articles and reports: 12-001-X201000211379

  Description:

  The number of people recruited by firms in Local Labour Market Areas provides an important indicator of the reorganisation of the local productive processes. In Italy, this parameter can be estimated using the information collected in the Excelsior survey, although it does not provide reliable estimates for the domains of interest. In this paper we propose a multivariate small area estimation approach for count data based on the Multivariate Poisson-Log Normal distribution. This approach will be used to estimate the number of firm recruits both replacing departing employees and filling new positions. In the small area estimation framework, it is customary to assume that sampling variances and covariances are known. However, both they and the direct point estimates suffer from instability. Due to the rare nature of the phenomenon we are analysing, counts in some domains are equal to zero, and this produces estimates of sampling error covariances equal to zero. To account for the extra variability due to the estimated sampling covariance matrix, and to deal with the problem of unreasonable estimated variances and covariances in some domains, we propose an "integrated" approach where we jointly model the parameters of interest and the sampling error covariance matrices. We suggest a solution based again on the Poisson-Log Normal distribution to smooth variances and covariances. The results we obtain are encouraging: the proposed small area estimation model shows a better fit when compared to the Multivariate Normal-Normal (MNN) small area model, and it allows for a non-negligible increase in efficiency.

  Release date: 2010-12-21

  ---

• 2. Small area estimation of average household income based on unit level models for panel data Archived

  Articles and reports: 12-001-X200700210496

  Description:

  The European Community Household Panel (ECHP) is a panel survey covering a wide range of topics regarding economic, social and living conditions. In particular, it makes it possible to calculate disposable equivalized household income, which is a key variable in the study of economic inequity and poverty. To obtain reliable estimates of the average of this variable for regions within countries it is necessary to have recourse to small area estimation methods. In this paper, we focus on empirical best linear predictors of the average equivalized income based on "unit level models" borrowing strength across both areas and times. Using a simulation study based on ECHP data, we compare the suggested estimators with cross-sectional model-based and design-based estimators. In the case of these empirical predictors, we also compare three different MSE estimators. Results show that those estimators connected to models that take units' autocorrelation into account lead to a significant gain in efficiency, even when there are no covariates available whose population mean is known.

  Release date: 2008-01-03

Journals and periodicals (0) (0 results)

No content available at this time.