Combining Census and Survey Data to Trace the Spatial Dimensions of Poverty
以厄瓜多尔为例，展示如何将抽样调查数据与普查数据结合，预测普查覆盖人口的贫困率，发现即使在较细的空间尺度上也能精确测量，但超过一定分解程度后标准误差会迅速上升。
Poverty maps provide information on the spatial distribution of living standards. They are an important tool for policymakers, who rely on them to allocate transfers and inform policy design. Poverty maps art also an important tool for researchers, who use them to investigate the relationship between distribution within a country and growth or other economic, environmental, or social outcomes. A major impediment to the development of poverty maps has been that needed data on income or consumption typically are available only from relatively small surveys. Census data have the required sample size but generally do not have the required information. This article uses the case of Ecuador to demonstrate how sample survey data can be combined with census data to yield predicted poverty rates for the population covered by the census. These poverty rates are found to be precisely measured, even at fairly disaggregated levels. However, beyond a certain level of spatial disaggregation, standard errors rise rapidly.