SAMPLE: SMALL AREA methods for poverty

and living condition estimates

Supported by the European Commission (FP7-SSH-2007-1).


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.

Official web site

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)