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SAMPLE: SMALL AREA methods for poverty and living condition estimates Supported by the European Commission (FP7-SSH-2007-1). |
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Summary: 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. NUTS2 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 target 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 SAMPLE project
is to identify and develop new indicators and models for inequality and
poverty with attention to social exclusion and deprivation, implement models,
measures and procedures for small area estimation of these 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. |
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Coordinator: Monica Pratesi (Università
di Pisa) Participants: Dipartimento di statistica e matematica applicata
all'Economia (Università di Pisa), Centro Interdipartimentale di ricerca
sulla Distribuzione del Reddito (Università di Siena), Cathie Marsh Centre
for Census and Survey Research (Crawford House), Departamento de Estadística
(Universidad Carlos III de Madrid), Centro de Investigación Operativa
(Universidad Miguel Hernández de Elche), Warsaw School of Economics,
Osservatorio Politiche Sociali (Provincia di Pisa), Simurg Ricerche, Glowny
Urzad Statystyczny (Poland) |