论文标题
偏远地区社会经济调查的有效分层方法
Efficient Stratification Method for Socioeconomic Survey in Remote Areas
论文作者
论文摘要
在印度尼西亚偏远地区实施对社会经济调查的采样设计时存在的问题是调查的高成本，低响应率和较少准确的成本。因此，需要开发采样设计，其中之一是提高分层程序的效率。可以通过模拟各种替代品数量和各种替代品样品分配来组合偏远地区的人口普查区块分层。福利浓度和地理难度层的层面是通过多对主要成分分析构建的。福利集中的地层旨在提高统计效率，而地理难度层则用于提高成本效率。估计程序在域级别和人口水平上执行。模拟研究通过使用2010年人口普查数据和2011年乡村效力数据来关注巴布亚省。某些采样方案可以分为四个象限，这是第一个具有较小的采样差异和低成本的象限，第二个象限具有较大的采样差异和低成本，第三个象限具有很大的采样差异和较高的成本，并且是第四个象限，具有小样本差异和高成本和高成本。基于这些仿真结果，获得了有效分层的几种替代方案，并获得了较小的采样差异和调查的低成本。
The problems that exist in implementing a sampling design for socio-economic surveys in remote areas in Indonesia are high cost of the survey, low response rate, and less accurate. Therefore, the sampling design needs to be developed, one of which is to improve the efficiency of the stratification procedure. Stratification of census block in remote areas can be developed by combining the strata of welfare concentration and the strata of geographic difficulty by simulating the various alternatives number of strata and the various alternatives sample allocation. The strata of welfare concentration and the strata of geographic difficulty are constructed by Polychoric Principal Component Analysis. The strata of welfare concentration aim to improve statistical efficiency, while the strata of geographic difficulty are used to improve cost efficiency. The estimation procedure is performed at the domain level and population level. The simulation study focus on Papua Province by using the 2010 Population Census data and the 2011 Village Potency data. Some sampling scenarios can be categorized into four quadrants, the first quadrant with small sampling variance and low cost, the second quadrant with big sampling variance and low cost, the third quadrant with big sampling variance and high cost, and the fourth quadrant with small sampling variance and high cost. Based on these simulation results, several alternative scenarios of efficient stratification with small sampling variance and low cost of the survey are obtained.
