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60 Volume LXV n. 1 – Gennaio-Marzo 2011 Riferimenti bibliografici BALLIN M., FALORSI P. D., RUSSO A. 2000. Condizioni di Coerenza e Metodi di Stima per le Indagini Campionarie sulle Imprese. Rivista di Statistica Ufficiale. 2000, n. 2, pp. 31- 52. CECCARELLI C., CUTILLO A. 2007. Il Trattamento della Mancata Risposta Totale nell'Indagine Eu-Silc: Una Valutazione Tramite una Misura del Cambiamento. Congiuntura. Udine: CREF, 1° trimetre, pp. 91-112. CECCARELLI C., DI MARCO M., RINALDELLI C. 2008. L'indagine Europea sui Redditi e le Condizioni di Vita delle Famiglie (It-silc). Metodi e Norme. Istat, 2008, n. 37. DEVILLE J. C., SÄRNDAL C.E. 1992. Calibration Estimators in Survey Sampling. Journal of the American Statistical Association. Giugno, 1992, vol. 87, n. 418, pp. 376-382. DEVILLE J. C., SÄRNDAL C. E., SAUTORY, O. 1993. Generalized Raking Procedures in Survey Sampling. Journal of the American Statistical Association. Settembre, 1993, vol. 88, n. 243, pp. 1013-1020. DEVILLE J.C. 1999. Simultaneous Calibration of Several Surveys.Proceedings of statistic Canada Symposium 99. Combining Data from Different Sources. Ottawa: Statistics Canada, Maggio 1999, pp. 207-212. LEMAÎTRE G., DUFOUR. J. 1987. An integrated method for Weighting Persons and Families. Survey Methodology. Dicembre, 1987, vol. 13, n. 2, pp. 199-207. SINGH A.C., MOHL C.A. 1996. Understanding Calibration Estimators in Survey Sampling. Survey Methodology. Dicembre, 1996, vol. 22 , n. 2, pp. 107-115. SUMMARY The Italian National Institute of Statistics (Istat) introduced in Survey on Income and Living Condition (It-Silc) several constraints from the Labor Force Survey (LFS) to produce estimation consistent with official source of working market and to correct further the no answer mechanism. The aim of this article is to find a variance expression of calibrated estimator with sample auxiliary variables in complex sampling designs, and to measure the impact of additional error introduced has on the total amount estimation of different type of income. _____________________ Claudio CECCARELLI, Primo Ricercatore, Istituto Nazionale di Statistica, Direzione centrale per le indagini su condizioni e qualità della vita, clceccar@istat.it Giovanni Maria GIORGI, Ordinario di Statistica, Università di Roma “La Sapienza”, Dipartimento di Scienze Statistiche, giovanni.giorgi@uniroma1.it Alessio GUANDALINI, Dottorando di Statistica, Università di Roma “La Sapienza”, Dipartimento di Scienze Statistiche, alessio.guandalini@uniroma1.it
Rivista Italiana di Economia Demografia e Statistica Volume LXV n. 1 – Gennaio-Marzo 2011 1. Introduction MULTIDIMENSIONAL POVERTY ACROSS EUROPE Martina Celidoni, Isabella Procidano, Luca Salmasi Recently the analysis of poverty has evolved towards a multidimensional perspective, considering not only the economic dimension, i.e. income or consumption, but also other attributes regarded as determinant for an acceptable living standard. The idea of enlarging the dimensions analysed is supported by several approaches: the basic-needs approach for instance regards poverty as lack of basic needs, also Sen’s capability approach sees poverty as inability of possession of a wide range of characteristics related to the living standard, while the social exclusion perspective argues that poverty can be considered as an exclusion of individuals from standard way of living and basic social activities. All those approaches criticize the uni-dimensional analysis because limiting and argue that focusing the attention on poverty only as lowness of income depicts an incomplete picture of the phenomenon, sometimes with misleading conclusions (Madden, 2008). With the aim of a more richer description of poverty in Europe, among elderly people, our paper adopts a multidimensional approach, considering as measure of well-being not only income but also health. Moreover the focus on elderly people is driven mainly by the fact that this part of the population has become relevant due to the substained aging process that Europe has occured in the last decades. We are interested therefore in comparing poverty across Europe, in terms of income and health, for a more and more preeminent part of the population. The development of multi-dimensional poverty is intrinsically motivated not only by the recognition that deprivation may occur in more than one dimension but also by the fact that the correlation between different dimensions of deprivation may not be perfect. If the aim is to identify poors and the correlation would be perfect in fact, the choice of the dimension upon which to measure the incidence of poverty is unimportant, since all dimensions will identify the same individuals as poor but if the degree of correlation between dimensions decreases, the case of a multi-dimensional approach becomes more persuasive (Madden, 2008). Using the Receiver Operating Characteristics curve (ROC) approach, we will examine the
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