标题： 小区域一般指标的非普查年估计 显示英文标题

标题： Small Area Estimation of General Indicators in Off-Census Years

摘要： 我们提出了一种在非人口普查年份的总体指标的小区域估计量，这些估计量避免使用过时的人口普查微观数据，但在人口普查年份中几乎是最优的。 该方法基于将过时的人口普查文件替换为一个覆盖感兴趣区域且包含有用辅助变量值的更大规模的单元级调查。 然而，所提出方法的最小数据要求是一次包含目标变量微观数据和适用于感兴趣时期的适当辅助变量的调查。 我们还开发了一个均方误差（MSE）估计量，该估计量考虑了使用大规模调查替代人口普查辅助信息所引入的不确定性。 我们的实证结果表明，当人口普查数据过时时，所提出的预测器明显优于其他预测器，并且当人口普查数据正确时，非常接近最优预测器。 它们还说明了所提出的总MSE估计量能够纠正不考虑大规模调查不确定性的纯模型MSE估计量的偏差。 显示英文摘要

摘要： We propose small area estimators of general indicators in off-census years, which avoid the use of deprecated census microdata, but are nearly optimal in census years. The procedure is based on replacing the obsolete census file with a larger unit-level survey that adequately covers the areas of interest and contains the values of useful auxiliary variables. However, the minimal data requirement of the proposed method is a single survey with microdata on the target variable and suitable auxiliary variables for the period of interest. We also develop an estimator of the mean squared error (MSE) that accounts for the uncertainty introduced by the large survey used to replace the census of auxiliary information. Our empirical results indicate that the proposed predictors perform clearly better than the alternative predictors when census data are outdated, and are very close to optimal ones when census data are correct. They also illustrate that the proposed total MSE estimator corrects for the bias of purely model-based MSE estimators that do not account for the large survey uncertainty.