Small area estimation has received considerable attention in recent years because of an increasing demand for small area statistics. Basic area level and unit level models have been studied in the literature to obtain empirical best linear unbiased predictors for small area means. Although this classical method is useful for estimating the small area means efficiently under strict model assumpt...

It is well-known that small area estimation needs explicit, or at least implicit use of models. These model-based estimates can differ widely from the direct estimates, especially for areas with very low sample sizes. While model-based small area estimates are very useful, one potential difficulty with such estimates is that when aggregated, the overall estimate for a larger geographical area m...

In this paper, some vital methodological issues of spatial microsimulation modelling for small area estimation have been addressed, with a particular emphasis given to the reweighting techniques. Most of the review articles in small area estimation have highlighted methodologies based on various statistical models and theories. However, spatial microsimulation modelling is emerging as a very us...

Poverty mapping is a valuable tool for governments and international organizations to identify the geographical areas population groups that are most deprived or vulnerable. This approach can lead designing monitoring development policies more effectively. article presents recent experience of Statistics Division UN Economic Commission Latin America Caribbean (ECLAC) in using Small Area Estimat...