INT 9505197 Lahiri Technical Description: This project provides partial support for Partha-sarathi Lahiri, University of Nebraska, to conduct statistical research in small-area estimation at the Indian Institute of Management, Calcutta with collaborator Rahul Mukherjee. Dr. Lahiri will also work with T.J. Rao of the Indian Institute of Statistics, Calcutta to explore new areas in survey sampling. Estimators used in large scale national sample surveys perform poorly at the sub-national level. The P.I. proposes to explore the use of empirical Bayes and hierarchical Bayes methods in developing estimators to generate reliable small area statistics. The collaborators will investigate whether this method which Lahiri has shown to be superior to the best linear estimators for small area means, holds for the general mixed model with random error variance components. They will extend the empirical Bayes and hierarchical Bayes methods to find estimators of small area characteristics for discrete data. Scope: Research in small area estimation is important for generating statistics at the state and county levels and for subgroups of the population. In India and the U.S., such statistics are needed by various federal and local governments for policy making and allocation of funds. The foreign collaborator has done outstanding work in the areas of Bayesian statistics, higher order asymptotics and survey sampling. Professor Mukherjee's recent advances in the area of asymptotics will be very helpful in proving difficult asymptotic results mentioned in the proposal. Many mutual benefits may be expected to result from this new collaborative activity. ***
