ABSTRACT

From the comprehensive appraisals of small area estimation methodologies in the previous chapters, it is clear that microsimulation modeling technology (MMT)-based spatial microsimulation modeling techniques can be very useful and efficient for small area estimation. The review of various methodologies also indicated that spatial microsimulation model-based indirect small area estimation has some significant advantages over the other statistical model-based indirect as well as direct estimation methods. For instance, the spatial microsimulation modeling techniques for small area estimation not only are robust and able to produce a point estimate but also can generate valuable spatial-scale microdatabases for further useful analyses as well as can determine confidence intervals (CIs) of the point estimates. These models can further measure the small area effects of policy changes.