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.
Field of science
- /social sciences/economics and business/economics/monetary and finances
Call for proposal
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Funding SchemeCP-FP - Small or medium-scale focused research project