SAMPLE

Small Area Methods for Poverty and Living Condition Estimates

Coordinatore	UNIVERSITA DI PISA    more  Organization address address: Lungarno Pacinotti 43/44 city: PISA postcode: 56126 contact info Titolo: Prof. Nome: Monica Cognome: Pratesi Email: send email Telefono: +39 50 2216252 Fax: +39 50 2216375
Nazionalità Coordinatore	Italy [IT]
Totale costo	953˙322 €
EC contributo	774˙972 €
Programma	FP7-SSH Specific Programme "Cooperation": Socio-economic Sciences and Humanities
Code Call	FP7-SSH-2007-1
Funding Scheme	CP-FP
Anno di inizio	2008
Periodo (anno-mese-giorno)	2008-03-01   -   2011-02-28

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	UNIVERSITA DI PISA  Organization address address: Lungarno Pacinotti 43/44 city: PISA postcode: 56126 contact info Titolo: Prof. Nome: Monica Cognome: Pratesi Email: send email Telefono: +39 50 2216252 Fax: +39 50 2216375	IT (PISA)	coordinator	203˙888.00
2	PROVINCIA DI PISA  Organization address address: P.ZZA VITTORIO EMANUELE II N. 14 city: PISA postcode: 56125 contact info Titolo: Dr. Nome: Paolo Cognome: Prosperini Email: send email Telefono: +39 050 929324 Fax: +39 050 929753	IT (PISA)	participant	129˙109.00
3	SIMURG CONSULENZE E SERVIZI DI MIRANI DANIELE SALVUCCI CLAUDIO E TOIGOMORENO SNC  Organization address address: VIA SANSONI EUGENIO 13 city: Livorno postcode: 57123 contact info Titolo: Dr. Nome: Moreno Cognome: Toigo Email: send email Telefono: +39 0586 210460 Fax: +39 0586 210460	IT (Livorno)	participant	84˙809.00
4	UNIVERSIDAD MIGUEL HERNANDEZ DE ELCHE  Organization address address: AVENIDA DE LA UNIVERSIDAD S/N city: ELCHE postcode: 3202 contact info Titolo: Mr. Nome: Rafael Cognome: Gandía-Balaguer Email: send email Telefono: +34 966 658 613	ES (ELCHE)	participant	78˙094.00
5	UNIVERSIDAD CARLOS III DE MADRID  Organization address address: CALLE MADRID 126 city: GETAFE (MADRID) postcode: 28903 contact info Titolo: Ms. Nome: Regina Cognome: García Beato Email: send email Telefono: +34 91 6249931 Fax: +34 91 6249930	ES (GETAFE (MADRID))	participant	66˙364.00
6	UNIVERSITA' DEGLI STUDI DI SIENA  Organization address address: VIA BANCHI DI SOTTO 55 city: SIENA postcode: 53100 contact info Titolo: Prof. Nome: Achille Cognome: Lemmi Email: send email Telefono: +39 0577 232624 Fax: +39 0577 232626	IT (SIENA)	participant	62˙603.00
7	SZKOLA GLOWNA HANDLOWA W WARSZAWIE  Organization address address: AL NIEPODLEGLOSCI 162 city: WARSZAWA postcode: 02 554 contact info Titolo: Mr. Nome: Artur Cognome: Mika Email: send email Telefono: +48 22 5649769 Fax: +48 22 5648616	PL (WARSZAWA)	participant	61˙016.00
8	UNIVERSITY OF SOUTHAMPTON  Organization address address: Highfield city: SOUTHAMPTON postcode: SO17 1BJ contact info Titolo: Ms. Nome: Yan Cognome: Qiao Email: send email Telefono: +44 23 80593907 Fax: +44 023 80596841	UK (SOUTHAMPTON)	participant	32˙026.00
9	CENTRUM EDUKACJI STATYSTYCZNEJ  Organization address address: Jachranka 81 city: Serock k. Warszawy postcode: 05-140 contact info Titolo: Ms. Nome: Katarzyna Cognome: Staniszewska Email: send email Telefono: +48 22 768 13 96 Fax: +48 22 768 14 94	PL (Serock k. Warszawy)	participant	28˙611.00
10	THE UNIVERSITY OF MANCHESTER  Organization address address: OXFORD ROAD city: MANCHESTER postcode: M13 9PL contact info Titolo: Mr. Nome: Matthew Cognome: Warrington Email: send email Telefono: +44 161 2752107 Fax: +44 161 2750968	UK (MANCHESTER)	participant	28˙452.00

Mappa

 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

 Obiettivo del progetto (Objective)

'It is well known that in order to ensure a good allocation of public funds and to guarantee the rights of final users of the statistics (government, research institutes and citizens) statistical data on monetary and supplementary poverty indicators have to be timely and effective. Effectiveness of statistical data is a function of their spatial relevance and accuracy. Often official data are referred only to wider domains (e.g. NUTS 2 level) and, sometimes, the finer is the required spatial detail (NUTS3, NUTS4 level) the less accurate is the estimate. Local Government has to know accurate data referred to local areas and/or small domains (NUTS3, NUTS4 level) to 1) ensure monitoring of Poverty and inequality; 2) focus on special targets consisting of segments of population at higher risk of poverty (elusive populations) 3) appreciate the multidimensional nature of poverty and inequality with attention to the non monetary aspects of it (social exclusion and deprivation) 4) measure the subjective aspects of poverty as they are perceived by local groups and populations. The aim of S.A.M.P.L.E. project is to identify and develop new indicators and models for inequality and poverty with attention to social exclusion and deprivation, as well as to develop, implement models, measures and procedures for small area estimation of the traditional and new indicators and models. This goal is achieved with the help of the local administrative databases. Local government agencies often have huge amount of administrative data to monitory some of the actions which witness situations of social exclusion and deprivation (social security claims for unemployment and eligibility for benefits from any of the programs Social Security administers) of households and citizens.'

Introduzione (Teaser)

Reliable statistics are essential for the EU's poverty-reduction strategies. Although extensive data exist at the national level, the picture becomes less clear on careful inspection. An EU-backed project developed indicators to measure poverty at the local level.

Descrizione progetto (Article)

Tackling poverty requires reliable, accurate and timely statistics. However, although high-quality data is available at the national level in Europe, it often happens that the finer the required spatial detail, the more blurred the resolution. This is a major challenge for local authorities and other stakeholders.

Financed by the Seventh Framework Programme (FP7), the 'Small area methods for poverty and living condition estimates' (SAMPLE) project sought to identify and develop new indicators and models for measuring inequality and poverty locally.

To achieve this, the project combined data from national surveys with data extracted from local administrative databases. This included information on benefit claimants and also involved the mining of data held by non-governmental organisations.

SAMPLE utilised widely used indicators on monetary and non-monetary poverty. Moreover, in collaboration with stakeholders working with the poor, the project developed new poverty indicators that meet local needs.

The results of the SAMPLE project will help local authorities and stakeholders to plan and implement their poverty-reduction policies. In fact, more than two thirds of stakeholders surveyed said that these local indicators would prove very useful in the planning of social policies.