论文标题
撒哈拉以南非洲的高分辨率贫困地图
High-Resolution Poverty Maps in Sub-Saharan Africa
论文作者
论文摘要
最新的贫困地图是政策制定者的重要工具，但到目前为止，生产价格昂贵。我们提出了一种可推广的预测方法，可以使用地理空间数据和机器学习算法在乡村层面产生贫困图。我们测试了25个撒哈拉以南非洲国家的拟议方法，并根据调查数据对其进行了验证。所提出的方法可以提高单个国家和越野估计的有效性，从而使44个撒哈拉以南非洲国家的贫困地图的精度高于以前。更重要的是，我们的越野估计可以使贫困地图在对新的全国性家庭调查不切实际或成本效益时，就像许多低收入和中等收入国家一样。
Up-to-date poverty maps are an important tool for policy makers, but until now, have been prohibitively expensive to produce. We propose a generalizable prediction methodology to produce poverty maps at the village level using geospatial data and machine learning algorithms. We tested the proposed method for 25 Sub-Saharan African countries and validated them against survey data. The proposed method can increase the validity of both single country and cross-country estimations leading to higher precision in poverty maps of 44 Sub-Saharan African countries than previously available. More importantly, our cross-country estimation enables the creation of poverty maps when it is not practical or cost-effective to field new national household surveys, as is the case with many low- and middle-income countries.
