Small area estimation techniques have typically relied on plug-in estimation based on models containing random area effects. More recently, regression M-quantiles have been suggested for this purpose, thus avoiding conventional Gaussian assumptions, as well as problems associated with the...

Unbiased direct estimators for small area quantities are usually considered too variable to be of any practical use. In this paper we propose a class of model-based direct estimators for small area quantities that appears to overcome this objection, in the sense that these estimators are...

Sample surveys are generally multivariate, in the sense that they collect data on more than one response variable. In theory, each variable can then be assigned an optimal weight for estimation purposes. However, it is a distinct practical advantage to have a single weight for all variables...

Microsimulation of business performance based on sample survey data is a relatively underdeveloped field, but its application in government economic policy formulation is potentially great since it can be used to measure the distributional effects of change rather than just average change....

The effective use of spatial information, that is the geographic locations of population units, in a regression model-based approach to small area estimation is an important practical issue. One approach for incorporating such spatial information in a small area regression model is via...

The effective use of spatial information, that is, the geographic locations of population units, in a regression model-based approach to small area estimation is an important practical issue. One approach for incorporating such spatial information in a small area regression model is via...

Small area estimation techniques typically rely on regression models that use both covariates and random effects to explain variation between the areas. However, such models also depend on strong distributional assumptions, require a formal specification of the random part of the model and do...