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<p>Livability has become a prominent topic in both academic discourse and policymaking. This paper investigates how societal stratification in livability varies based on residual income and the provision of social infrastructure and explores the factors that drive these differences. Initially, we calculate the residual income for households across different regions of Austria. Subsequently, we create a composite indicator to measure the availability and accessibility of social infrastructure in each municipality. Using a Finite Mixture Model (FMM), we analyze how households group based on these factors and employ a Bayesian multinomial logistic model to identify the socioeconomic variables such as household composition, education, and employment status that influence cluster membership. The results reveal significant clustering related to residual income and social infrastructure provision, indicating clear societal stratification in livability. Socioeconomic variables and regional context notably influence this clustering. Our findings highlight important implications, particularly regarding the potential impact of privatizing public services on residual income, especially for low-income households that may be more dependent on public social infrastructure.</p>

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Stratification of Livability: A Framework for Analyzing Differences in Livability Across Income, Consumption, and Social Infrastructure

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月21日

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  • Tatjana Neuhuber,
  • Antonia E. Schneider

摘要

Livability has become a prominent topic in both academic discourse and policymaking. This paper investigates how societal stratification in livability varies based on residual income and the provision of social infrastructure and explores the factors that drive these differences. Initially, we calculate the residual income for households across different regions of Austria. Subsequently, we create a composite indicator to measure the availability and accessibility of social infrastructure in each municipality. Using a Finite Mixture Model (FMM), we analyze how households group based on these factors and employ a Bayesian multinomial logistic model to identify the socioeconomic variables such as household composition, education, and employment status that influence cluster membership. The results reveal significant clustering related to residual income and social infrastructure provision, indicating clear societal stratification in livability. Socioeconomic variables and regional context notably influence this clustering. Our findings highlight important implications, particularly regarding the potential impact of privatizing public services on residual income, especially for low-income households that may be more dependent on public social infrastructure.