1,721,075 research outputs found
A comparison of adjusted Bayes estimators of an ensemble of small area parameters
No full textEmpirical and Hierarchical Bayes methods are often used to improve the precision of design-based estimators in small area estimation problems. By the way, when posterior means are used to estimate the elements of an 'ensemble' of parameters (such as the means of a target variable in a collection of small areas), a poor estimate of the empirical distribution function of the ensemble typically results. Several adjusted estimators have been proposed in the literature in order to obtain better estimates of the empirical distribution function and other nonlinear functions of an ensemble of parameters. In this paper we discuss a set of adjusted estimators for the univariate Fay-Herriot model according to Hierarchical Bayesian solutions. The repeated sampling properties of the considered estimators and the associated measures of uncertainty are evaluated by means of a simulation exercise under the assumption of normality. We also explore the properties of the considered adjusted estimators when normality of random effects fails
Robust models for mixed effects in linear mixed models applied to Small Area Estimation
Get PDFHierarchical models are popular in many applied statistics fields including
Small Area Estimation. A well known model in this field is the
Fay-Herriot model, in which unobservable parameters are assumed Gaussian.
In Hierarchical models assumptions about unobservable quantities
are difficult to check. Sinharay and Stern (2003) for a special case of
the Fay-Herriot model, showed that violations of the assumptions about
the random effects are difficult to assess using posterior predictive checks.
They conclude that this may represent a form of model robustness . In
this paper we consider two extensions of the Fay-Herriot model in which
the random effects are supposed to be distributed according to either an
Exponential Power (EP) distribution or a skewed EP distribution. The
aim is to explore the robustness of the Fay-Herriot model for the estimation
of individual area means as well as the Empirical Distribution
Function of their ’ensemble’. Based on a simulation experiment our findings
are largely consistent with those of Sinharay and Stern as far as the
efficient estimation of individual small area parameters is concerned. On
the contrary, when the aim is the estimation of the Empirical Distribution
Function of the ’ensemble’ of small area parameters, results are more
sensitive to the failure of distributional assumptions
A design-based approximation to the BIC in finite population sampling
Get PDFIn this article, various issues related to the implementation of the usual
Bayesian Information Criterion (BIC) are critically examined in the context of
modelling for finite populations. A suitable design-based approximation to the BIC
is proposed in order to avoid the derivation of the exact likelihood of the sample
which is often very complex in a finite population sampling. The approximation is
justified using a theoretical argument and a Monte Carlo simulation study
Estimation of poverty indicators at the sub-national level using multivariate small area models
No full textIn recent years, the measure of regional disparities on poverty and social exclusion has received increasing attention by policy makers and this has produced a growing demand of sub-national statistical information on income parameters. Taking into account the multidimensionality of this phenomenon, in the Laeken European Council (Eurostat, 2003) a set of financial poverty indicators were suggested to monitor the progress in fighting inequality. In the European Union regional statistical information on income can be obtained from the European Community Household Panel, a survey designed to provide reliable estimates for large regions in the countries. The aim of this work is to estimate at sub-national level some of the income indicators suggested in the Laeken council. We propose Bayesian small area estimators based on multivariate area level models exploiting the correlation between different indicators. The tendency of model based estimates to over-shrink towards the synthetic component can be a draw-back for policy makers interested in capturing regional disparities in financial poverty. To preserve the relationship between different indicators and disparities over areas, we adopt a multivariate constrained Bayes estimator. The comparison between results based on different models allows us to select the estimator realizing the best compromise between gain in efficiency and reduction of the over-shrinkage
The determinants of Labour Market transitions
No full textThis paper focuses on changes in the Italian labour market over the decade 1993-2003.
We estimate both aggregate transition matrices and micro-level multinomial logistic regression
models to analyse flows between labour market states and their determinants.
We aim to assess whether labour market intervention and regulation introduced in the
nineties acted in the expected direction, that is helping disadvantaged categories such as
women and the young. We find that, at least as far as our analysis goes, this has not been
the case
A Comparison of Adjusted Bayes Estimators of use in Small Area Estimation
Get PDFEmpirical and Hierarchical Bayes methods are often used to improve the precision design-based estimators in Small Area estimation problems. By the way, when posterior means are used to estimate an 'ensemble' of parameters, a poor estimate of the empirical distribution function of the ensemble typically results. Several adjusted estimators have been
proposed in the literature in order to obtain better estimates of nonlinear function of an ensemble of parameters. In this paper we discuss a set of adjusted estimators with reference to the univariate and multivariate Fay- Herriot models within the framework of Hierarchical Bayesian modeling. The repeated sampling properties of the considered estimators and the
associated measures of uncertainty are evaluated by means of a simulation exercise
Small area estimation of the Gini concentration coefficient
No full textThe Gini coefficient is a popular concentration measure often used in the analysis of
economic inequality. Estimates of this index for small regions may be useful to properly
represent inequalities within local communities. However, the small area estimation for
the Gini coefficient has not been thoroughly investigated. A method based on area level
models, thereby avoiding the assumption of the availability of Census data at the micro
level, is proposed. A modified design based estimator for the coefficient with reduced small
sample bias is suggested as input for the small area model, while a hierarchical Beta mixed
regression model is introduced to combine survey data and auxiliary information. The
methodology is illustrated by means of an example based on Italian data from the European
Union Survey on Income and Living Conditions
A stratified model for the assessment of meteorologically adjusted trends of surface ozone
No full textWe consider the problem of assessing long-term trends of ozone concentrations measured on a single site located in an urban area. Among the many methods proposed in the literature to eliminate the confounding effect of changing weather conditions, we employ a stratification of daily maxima based on regression trees. Within each stratum conditional independence and Weilbull distribution are assumed for maxima. Long-term trend is defined non-parametrically by the sequence of yearly medians. Models are estimated following the Bayesian approach.
The alternative assumptions of common and stratum specific trends are compared and a model with common trend for all strata is selected for the analyzed real dataset. The conditional independence assumption is checked by the comparison with a model including an autoregressive component
Unemployment outflows: the relevance of gender and marital status in Italy and Spain
No full textPurpose – The purpose of this paper is to shed light on transitions from the state of unemployment to
that of employment and of inactivity in Italy and Spain.
Design/methodology/approach – First, the paper investigates the determinants of unemployment
outflows in these two Mediterranean labour markets. Then, the paper examines discrepancies and
similarities between specific outflow determinants, especially the interactions between gender and
marital status, by comparing results obtained across countries.
Findings – The findings of the paper suggest that gender and marital status influence the probability
of unemployment outflows in both countries, although not in the same way, especially with reference
to marital status. Discrepancies also emerge in relation to the role of geographical area of residence.
Originality/value – International comparisons of unemployment outflows are rather new in the
literature, and as far as we know none have been performed using European Union Statistics on
Income and Living Conditions data. Further, although studies quite often examine the issue of
gender-related labour mobility using the European Community Household Panel survey that took
place in the 1990s (Arulampalam et al., 2007; Garcia Pe ́rez and Rebollo Sanz, 2005; Theodossiou
and Zangelidis, 2009), one of the main contributions of this paper is that it provides a systematic
examination of the issue, considering the influence of gender and marital status differences on patterns
of unemployment outflows to employment and inactivity
- …
