<p>The official poverty measure of the United States remains unequipped to appropriately capture poverty across America. As a result, the Supplemental Poverty Measure (SPM) has increasingly supplanted the official measure in policy analysis and statistics. A primary point of conflict among poverty-focused scholars regarding the SPM is its current geographic adjustment, which adjusts poverty thresholds at three spatial scales: identified metropolitan areas, unidentified metropolitan areas by state, and nonmetropolitan areas by state. Pooling all nonmetropolitan counties within each state into a single adjustment is believed to be responsible for the ‘flip’ in the rural-urban poverty differential between the official measure and the SPM. Using federally restricted data, we address this conflict and generate novel estimates of the SPM using county-specific, hybrid, and commuting-zone geographic adjustments. Our estimates illustrate the role of the current adjustment in our understanding of rural-urban poverty, while also demonstrating the utility of our preferred commuting-zone-level adjustment.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

The Impact of Precise Geographic Adjustments on the Supplemental Poverty Measure

  • J. Tom Mueller,
  • Darcy L. Sullivan,
  • Matthew M. Brooks,
  • Regina S. Baker

摘要

The official poverty measure of the United States remains unequipped to appropriately capture poverty across America. As a result, the Supplemental Poverty Measure (SPM) has increasingly supplanted the official measure in policy analysis and statistics. A primary point of conflict among poverty-focused scholars regarding the SPM is its current geographic adjustment, which adjusts poverty thresholds at three spatial scales: identified metropolitan areas, unidentified metropolitan areas by state, and nonmetropolitan areas by state. Pooling all nonmetropolitan counties within each state into a single adjustment is believed to be responsible for the ‘flip’ in the rural-urban poverty differential between the official measure and the SPM. Using federally restricted data, we address this conflict and generate novel estimates of the SPM using county-specific, hybrid, and commuting-zone geographic adjustments. Our estimates illustrate the role of the current adjustment in our understanding of rural-urban poverty, while also demonstrating the utility of our preferred commuting-zone-level adjustment.