Scholarlink

<p>Detailed distributional estimates at finer geographical levels remain scarce, despite their critical relevance for household well being and policy intervention. This paper leverages Italian income tax records dating back to 1976, focusing on top income concentration and inequality across the country’s regions, macro-areas, and the recently introduced classification of the National Strategy for Inner Areas (SNAI). Our analysis reveals a persistent rise in income concentration over the past few decades, particularly among the top earners, while also highlighting nuanced regional and sub-regional dynamics. Notably, city size plays a crucial role, with larger cities experiencing a more pronounced level of income concentration compared to smaller ones. Southern regions exhibit lower income concentration levels among the top income groups, emphasizing the need for disaggregated analyses to capture these complexities accurately.</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

A new geography of inequality: top incomes in Italian Regions and Inner Areas

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月20日

查看全文
  • Demetrio Guzzardi,
  • Salvatore Morelli

摘要

Detailed distributional estimates at finer geographical levels remain scarce, despite their critical relevance for household well being and policy intervention. This paper leverages Italian income tax records dating back to 1976, focusing on top income concentration and inequality across the country’s regions, macro-areas, and the recently introduced classification of the National Strategy for Inner Areas (SNAI). Our analysis reveals a persistent rise in income concentration over the past few decades, particularly among the top earners, while also highlighting nuanced regional and sub-regional dynamics. Notably, city size plays a crucial role, with larger cities experiencing a more pronounced level of income concentration compared to smaller ones. Southern regions exhibit lower income concentration levels among the top income groups, emphasizing the need for disaggregated analyses to capture these complexities accurately.