Improved Direct Estimators for Small Areas

Unbiased direct estimators for small area quantities are usually considered too variable to be of any practical use. This book described a class of model based direct estimators (MBDE) for small area quantities that appears to overcome this objection, in the sense that these estimators are comparable in efficiency to the indirect model-based small area estimators that are now widely used. There are many practical advantages associated with such MBDE estimators, arising from the fact that they are computed as weighted linear combinations of the actual sample data from the small areas of interest. In this case the weights borrow strength via a model that explicitly allows for small area effects. An extension of the MBDE approach to multipurpose weighting based small area estimation is also discussed. The MBDE approach to small area estimation for skewed data where the linear model provides poor fit and standard methods of small area estimation are inefficient is also considered.

Autorentext

Hukum Chandra is working as Senior Scientist at Indian Agricultural Statistics Research Institute, New Delhi. He did Ph.D. from the University of Southampton and Post Doctorate from the University of Wollongong. He is recipient of Commonwealth Scholarship, U.K. and prestigious Cochran-Hansen Award 2009 by the IASS.