Spatial information and geoadditive small area models

Combining the need of small area estimation methods for skewed variables with the flexibility of a semi-parametric model, this study discusses a recent approach to identify and include the spatial pattern in small area estimation. Thus, the estimated spatial patterns reflect the propensity of the considered characteristic in a region, after controlling for other unit-level effects. In particular, the work focuses on socio-economic data collected by the World Bank program on Living Standard Measurement Study (LSMS) (Grosh and Glewwe 2000). The program is designed to assist policymakers in their efforts to identify how policies could be designed and improved to positively affect outcomes in health, education, economic activities, housing and utilities, etc. We combine the model parameters estimated using the dataset of the 2002 Living Standard Measurement Study with the 2001 Population and Housing Census covariate information and we apply a geoadditive small area estimation model in order to estimate the district level mean of the household per-capita consumption expenditure for the Republic of Albania.