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Modeling of income and indicators of poverty and social exclusion using the Generalized Beta Distribution of the Second Kind

Monique Graf & Desislava Nedyalkova

Résumé There are three reasons why estimation of parametric income distributions may be useful when empirical data and estimators are available: to stabilize estimation; to gain insight into the relationships
between the characteristics of the theoretical distribution and a set of indicators, e.g. by sensitivity plots; and to deduce the whole distribution from known empirical indicators, when the raw data are not
available. The European Union Statistics on Income and Living Conditions (EU-SILC) survey is used to address these issues. In order to model the income distribution, we consider the generalized beta distribution of the second kind (GB2). A pseudo-likelihood approach for fitting the distribution is considered, which takes into account the design features of the EU-SILC survey. An ad-hoc procedure for robustification of the sampling weights, which improves estimation, is presented. This method is compared to a non-linear fit from the indicators. Variance estimation within a complex survey setting
of the maximum pseudo-likelihood estimates is done by linearization (a sandwich variance estimator), and a simplified formula for the sandwich variance, which accounts for clustering, is given. Performance
of the fit and estimated indicators is evaluated graphically and numerically.
   
Mots-clés income distribution, inequality, maximum pseudo-likelihood estimation, monetary indicators, sandwich variance estimator
   
Citation Graf, M., & Nedyalkova, D. (2014). Modeling of income and indicators of poverty and social exclusion using the Generalized Beta Distribution of the Second Kind. Review of Income and Wealth, 60(4), 821-842.
   
Type Article de périodique (Anglais)
Date de publication 2-12-2014
Nom du périodique Review of Income and Wealth
Volume 60
Numéro 4
Pages 821-842
URL http://onlinelibrary.wiley.com/doi/10.1111/roiw.2014.60.i...
Liée au projet Convention Université de Neuchâtel/Office fédéral de la s...