A New Chain Ratio-Ratio-Type Exponential Estimator Using Auxiliary Information in Sample Surveys

Abstract

This paper advocates the problem of estimating the finite population mean using auxiliary information in sample surveys. We have suggested a new chain ratio-ratio- type exponential estimator and its properties are studied up to first degree of approximation. It has been shown that the proposed estimator is more efficient than the usual unbiased estimator, classical ratio estimator, Bahl and Tuteja [1] ratio-type exponential estimator and Kadilar and Cingi [3] chain ratio-type estimator under very realistic condition. Generalized version of the suggested chain ratio-ratio-type estimator is also given along with its properties. An empirical study is given in support of the present study.