Chao Li-Wei, Szrek Helena, Peltzer Karl, Ramlagan Shandir, Fleming Peter, Leite Rui, Magerman Jesswill, Ngwenya Godfrey B, Pereira Nuno Sousa, Behrman Jere
Population Studies Center, University of Pennsylvania, 3718 Locust Walk, Room 239, Philadelphia, Pennsylvania 19104-6298, U.S.A.
J Dev Econ. 2012 May 1;98(1):94-107. doi: 10.1016/j.jdeveco.2011.08.007. Epub 2011 Sep 6.
Finding an efficient method for sampling micro- and small-enterprises (MSEs) for research and statistical reporting purposes is a challenge in developing countries, where registries of MSEs are often nonexistent or outdated. This lack of a sampling frame creates an obstacle in finding a representative sample of MSEs. This study uses computer simulations to draw samples from a census of businesses and non-businesses in the Tshwane Municipality of South Africa, using three different sampling methods: the traditional probability sampling method, the compact segment sampling method, and the World Health Organization's Expanded Programme on Immunization (EPI) sampling method. Three mechanisms by which the methods could differ are tested, the proximity selection of respondents, the at-home selection of respondents, and the use of inaccurate probability weights. The results highlight the importance of revisits and accurate probability weights, but the lesser effect of proximity selection on the samples' statistical properties.
为研究和统计报告目的找到一种对微型和小型企业(MSE)进行抽样的有效方法,在发展中国家是一项挑战,因为这些国家往往没有MSE的登记册或登记册已过时。缺乏抽样框架给找到具有代表性的MSE样本造成了障碍。本研究使用计算机模拟从南非茨瓦内市的企业和非企业普查中抽取样本,采用三种不同的抽样方法:传统概率抽样方法、紧凑段抽样方法和世界卫生组织扩大免疫规划(EPI)抽样方法。测试了这些方法可能存在差异的三种机制,即受访者的就近选择、受访者的上门选择以及使用不准确的概率权重。结果突出了回访和准确概率权重的重要性,但就近选择对样本统计特性的影响较小。