Sabato 15 settembre scorso, a Siena, è mancato il Prof. Vijay Verma, Honorary fellow del Centro ASESD Camilo Dagum.
Punto di riferimento costante per la ricerca in Survey Methodology e Survey Sampling, nel corso della sua lunga e proficua carriera, ha collaborato con molti organismi internazionali e formato instancabilmente numerosi giovani ricercatori.
Vijay ha insegnato in Italia presso l’Università di Siena come Professore a contratto, partecipando costantemente alle attività di ricerca dell’Università e del Centro Interuniversitario.
Lo ricordiamo con profondo affetto, stima e gratitudine per il valore di tutti i suoi insegnamenti e consigli.
Vijay Verma: Poverty: Cross-sectional, multimensional, longitudinal
Workshop Jean Monnet SAMPLEU “Small Area Methods and living conditions indicators in European poverty studies in the era of data deluge and Big data”Table 2. Multidimensional poverty at a local level how to synthetize the dimensions? – 28 Maggio 2018
Il 19 settembre 2018 alle ore 16.30 è convocata per via telematica la riunione del Consiglio Scientifico del Centro Interuniversitario di Ricerca e Servizi sulla Statistica Avanzata per lo Sviluppo Equo e Sostenibile – Camilo Dagum /Tuscan Universities Research Centre – Camilo Dagum on Advanced Statistics for the Equitable and Sustainable Development- ASESD. A seguire si terrà la riunione del Comitato di Gestione.
Ordine del Giorno
The 12th International Conference on Computational and Financial Econometrics (CFE 2018) and the 11th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2018) will take place jointly at the University of Pisa, Italy, 14-16 December 2018,
Tutorials will be given on Thursday 13th of December 2018 and the CRoNoS Winter Course on Time Series will take place the 11-12 December 2018.
The abstract submission is extended until the 12th of September.
For more information visit:
M. Pratesi: La misura della povertà educativa
Giusti, C., Masserini, L., & Pratesi, M. (2017). Local Comparisons of Small Area Estimates of Poverty: An Application Within the Tuscany Region in Italy. Social Indicators Research, 131(1), 235-254.
The aim of this paper is to highlight some key issues and challenges in the analysis of poverty at the local level using survey data. In the last years there was a worldwide increase in the demand for poverty and living conditions estimates at the local level, since these quantities can help in planning local policies aimed at decreasing poverty and social exclusion. In many countries various sample surveys on income and living conditions are currently conducted, but their sample size is not enough to obtain reliable estimates at local level. When this happens, small area estimation (SAE) methods can be used. In this paper, a SAE model is used to compute the mean household equivalised income and the head count ratio for the 57 Labor Local Systems of the Tuscany region in Italy for the year 2011. The caveats of the analysis of poverty at the local level using small area methods are many, and some are still not so well explored in the literature, starting from the definition of the target indicators to the relevant dimensions of their measurement. We suggest in this paper that together with the universally recognized multidimensional, longitudinal and local dimensions of poverty, a new dimension must be considered: the price dimension, which should take into account local purchasing power parities to correctly compare the poverty indicators based on income measures.
Biggeri L. & Pratesi M. (2017), Monetary poverty indicators at local level: definitions, methods of estimations and comparisons in real term, International Statistical Institute Congress, Morocco, 2017
The importance of poverty measures (indicators and number of poor) at sub-national level is widely attested. Particularly, the local poverty indicators are relevant both for a detailed planning of the policy actions against poverty and social exclusion and for the citizens to evaluate their effect. However, there are still open problems to compute adequate sub national poverty indicators. They refer to: 1) the definition of poverty lines; 2) the methods for accounting the spatial variation of cost of living to make comparisons in real terms between different areas; 3) the use of Small Area Estimation methods when sample size is not enough to obtain accurate estimates of the indicators at local level. In this paper, we discuss all these problems in a coherent way, presenting analyses on the impact of the different choices on the value of poverty rates for the 20 Italian Regions and computing the estimations of the poverty rates at the sub-regional level by using SAE methods. The key results underlined the strong differences in the territorial distribution of poor by using national specific versus sub-national specific poverty lines, while the effect of the heterogeneity of the spatial price indexes seems less important.
Gianni Betti presentation at the 49th Meeting of the Italian Statistical Society (SIS) – University of Palermo 20-22 June 2018: “Can a neighbour region influence poverty? A fuzzy and longitudinal approach” (Gianni Betti, Federico Crescenzi, Francesca Gagliardi 1) – Contributed Session “Social Indicators” (21.06.2018)
Betti – Crescenzi – Gagliardi sis2018
TREDICESIMA CONFERENZA NAZIONALE DI STATISTICA
Dall’incertezza alla decisione consapevole, un percorso da fare insieme
La Tredicesima Conferenza nazionale di statistica si svolge a Roma dal 4 al 6 luglio 2018 presso il Centro Congressi Ergife Palace (Via Aurelia, 619 – 00165 Roma)
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Gaia Bertarelli presentation at the 49th Meeting of the Italian Statistical Society (SIS) – University of Palermo 20-22 June 2018: “Integration of socio-economic data for the estimation of indicators at municipal level ” (G. Bertarelli, S. Casacci, M. D’Alò, D. Ercolani, A. Guandalini, A. Fasulo, M. G. Ranalli, F. Solari) – Solicited Session “Supporting Regional Policies Through Small Area Statistical Methods” (22.06.2018)
Download Bertarelli SIS2018