The session – granted by the Tuscan Interuniversity Centre Advanced Statistics for Equitable and Sustainable Development “Camilo Dagum” (http://www.centrodagum.it) – aims at highlighting the importance and relevance of local data in welfare studies focusing on the limits and the potentialities of SAE methods in producing new data on welfare and wellbeing indicators at local level.
The session addresses three topics under open discussion:
i) The production and use of the Purchase Power Parities in regional studies on poverty.
ii) The estimation of indicators of poverty by SAE taking into account how the left tail of the income distribution is shaped.
iii) The possibility that the exploited relationship between response variable and covariates in SAE differs between different types of areas
Trudi Renwick, (Assistant Division Chief Economic Characteristics Social, Economic and Housing Statistics Division U.S. Census Bureau ) will present a paper on the necessity to study poverty at local level, with a focus on the problems (comparablity issues, prices, Poverty Lines….) and a review of what the division of the U.S. census Bureau is doing
on this. Bettina Aten and Eric Figueroa will coauthor the paper.
Maria Rosaria Ferrante, (Full Professor in Economic Statistics at the University of Bologna)
will present a paper with E. Fabrizi and C, Trevisano on Small Area Estimation of the relative Median Poverty Gap.
Charlotte Articus, (PhD, Junior researcher in Statistics at the University of Trier)
will present a paper with Burgard, J. P.; and Münnich, R. on Concomitant Variable Mixture Models for Small Area Estimation: An Application to Estimating Regional ARPRs in Germany.
The session should be of interest to many SAE 2017 attendees because the SAE measures of poverty level, the number of people in poverty and of all the poverty indicators are included in the Sustainable Development Goals of the United Nations and involve all academic and official statisticians.
The objective is to discuss on SAE methods to obtain spatial comparable measures of the poverty and living conditions.