نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
Economic-social indicators such as unemployment rate and economic participation rate, as key measures for assessing community development, have consistently been a focal point for policymakers. This study aims to address the urgent need of decision-makers for accurate unemployment rate estimates at the county level in Isfahan Province, which is challenging due to its economic diversity and migration patterns. It introduces a novel small area estimation method based on synthetic data, combining the 1395 census data with labor force survey data from 1396 to 1402 to simulate the province's synthetic population. This approach, utilizing advanced statistical algorithms while preserving data privacy, eliminates the need for costly editing and imputation processes, enabling high-precision sub-regional estimates. Findings indicate that this model not only facilitates seasonal monitoring of labor force indicators at a micro-geographical level but also provides a practical solution to overcome limitations of traditional sampling methods, contributing to the timely updating of the national statistical system and enhancing local policymaking.
کلیدواژهها English
