This paper analyses the distribution of purchasing power standardized per capita income across EU-12 regions between 1977 and 1996. Dispersion of incomes between regions is measured taking into account their population sizes. The cross-sectional distributions are initially described by weighted kernel density estimates, revealing a multimodal structure of the distributions, less evident over the period. This evidence is supported by a bootstrap test. To detect homogeneous groups of regions, the empirical distributions are approximated by a finite mixture of normal densities. The components of the mixture represent clusters of poor/rich regions, while the mixing proportions the allocation over the poor and the rich components. The number of components is assessed by a bootstrap LR test, and the goodness of fit by a kernel density-based test. Income mobility is modelled by the stochastic kernel, the continuous counterpart of the transition probability matrix. The main implication is a very slow process of catching up of the poorest regions with the richer ones and a process of shifting away of a small group of very rich regions. This evidence is reflected in the shape of the ergodic distribution, which is well fitted by a two-component mixture model. Copyright (c) 2006 John Wiley & Sons, Ltd.
Empirical evidence of income dynamics across EU regions / Pittau, Maria Grazia; Zelli, Roberto. - In: JOURNAL OF APPLIED ECONOMETRICS. - ISSN 0883-7252. - STAMPA. - 21:5(2006), pp. 605-628. [10.1002/jae.855]
Empirical evidence of income dynamics across EU regions
PITTAU, Maria Grazia;ZELLI, Roberto
2006
Abstract
This paper analyses the distribution of purchasing power standardized per capita income across EU-12 regions between 1977 and 1996. Dispersion of incomes between regions is measured taking into account their population sizes. The cross-sectional distributions are initially described by weighted kernel density estimates, revealing a multimodal structure of the distributions, less evident over the period. This evidence is supported by a bootstrap test. To detect homogeneous groups of regions, the empirical distributions are approximated by a finite mixture of normal densities. The components of the mixture represent clusters of poor/rich regions, while the mixing proportions the allocation over the poor and the rich components. The number of components is assessed by a bootstrap LR test, and the goodness of fit by a kernel density-based test. Income mobility is modelled by the stochastic kernel, the continuous counterpart of the transition probability matrix. The main implication is a very slow process of catching up of the poorest regions with the richer ones and a process of shifting away of a small group of very rich regions. This evidence is reflected in the shape of the ergodic distribution, which is well fitted by a two-component mixture model. Copyright (c) 2006 John Wiley & Sons, Ltd.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.