Estimating economic poverty indicators at the local level is essential for well-targeted data-driven welfare policies. However, Italy is a country characterized by strong geographical heterogeneity represented by unequal price levels among different areas, and computing poverty indicators with a national monetary poverty threshold can be misleading. This work proposes a novel approach to estimate monetary poverty incidence at the provincial level in Italy considering the different price levels within national boundaries. To account for local price variation, Spatial Price Indices (SPIs) are computed using scanner data on retail prices. The SPIs are estimated in two ways, referring to the mean local prices and using the 20th percentile of the prices. These two kinds of SPIs are used to adjust the national poverty line when computing the poverty incidence at the provincial level using Small Area Estimation (SAE) models. Our findings suggest that adjusting the national poverty line using the SPIs to compute a monetary poverty index can modify the poverty mapping results from the map produced with the traditional national poverty line that ignores price differences.

估算地方一级的经济贫困指标对于有针对性的数据驱动的福利政策至关重要。然而，意大利是一个地理异质性很强的国家，不同地区之间的物价水平不平等，用国家货币贫困线计算贫困指标可能会产生误导。这项工作提出了一种新颖的方法来估计意大利省级货币贫困发生率，考虑到国内不同的价格水平。为了考虑当地价格变化，空间价格指数（SPI）是使用零售价格的扫描数据计算的。SPI 通过两种方式估算，即参考当地平均价格和使用价格的第 20 个百分位。这两种SPI用于在使用小区域估计（SAE）模型计算省级贫困发生率时调整国家贫困线。我们的研究结果表明，使用 SPI 来计算货币贫困指数来调整国家贫困线可以修改使用忽略价格差异的传统国家贫困线绘制的地图的贫困测绘结果。