A RECOMMENDATION ON ESTIMATING PROVINCIAL UNEMPLOYMENT RATE

Abstract

Due to budget and time constraints, the National Statistical Organizations usually design their surveys and optimize the size of samples at a larger geographical level e.g. the national level. This causes the economic researchers, planners, and decision-makers not to have access to their required data at the smaller geographical levels or in terms of some specific characteristics.In order to meet their statistical needs, the data users have resorted to the other agencies producing statistics which design their surveys and optimize size of samples at a smaller geographical level such as Ostan (province). Unfortunately this could impose a heavy cost on the country's budget, lengthen the process of data collection and dissemination and bring about the non-sampling errors with a higher proportion in the process. This paper, introducing some Small Area Estimation (SAE) methods, attempts to recommend an appropriate method, for estimating unemployment rates at the provincial level.

Keywords

• empirical bayes estimator
• indirect estimator
• structure preserving estimation (spree)
• synthetic estimator
• post-strata
• small area