TY - JOUR
TI - Modeling of income and indicators of poverty and social exclusion using the Generalized Beta Distribution of the Second Kind
UR - http://onlinelibrary.wiley.com/doi/10.1111/roiw.2014.60.issue-4/issuetoc;jsessionid=ABF2EA1C91AB811BE0A7E452FD690C10.f01t01
KW - income distribution, inequality, maximum pseudo-likelihood estimation, monetary indicators, sandwich variance estimator
LA - en
AU - Graf, M.
AU - Nedyalkova, D.
PY - 2014
DA - 2.12
AB - 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.
T2 - Review of Income and Wealth
IS - 4
VL - 60
SP - 821
EP - 842
ER -