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This chapter presents the food-based statistical approach as the most algorithmic and resource-efficient strategy to measure absolute poverty in the European context. The approach is based on the statistical analysis of household expenditure patterns and uses a novel set of nutritional food reference budgets as input to determine the non-food component of the poverty threshold. This is an established measurement procedure in developing countries, but is not directly applicable in advanced economies characterised by low food expenditure shares. A significant part of the chapter is therefore devoted to presenting a new simulation-based inverse methodology that circumvents the related limitations and produces reliable and consistent poverty estimates for all EU countries.

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Food-Based Statistical Approach to Absolute Poverty Measurement

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Balint Menyhert,
  • Zsombor Cseres-Gergely,
  • Virmantas Kvedaras,
  • Benedetta Mina,
  • Filippo Pericoli,
  • Slavica Zec

摘要

This chapter presents the food-based statistical approach as the most algorithmic and resource-efficient strategy to measure absolute poverty in the European context. The approach is based on the statistical analysis of household expenditure patterns and uses a novel set of nutritional food reference budgets as input to determine the non-food component of the poverty threshold. This is an established measurement procedure in developing countries, but is not directly applicable in advanced economies characterised by low food expenditure shares. A significant part of the chapter is therefore devoted to presenting a new simulation-based inverse methodology that circumvents the related limitations and produces reliable and consistent poverty estimates for all EU countries.