Rethinking poverty attribution typologies in contemporary China: A latent class analysis beyond the internal–external dichotomy

Abstract China has eradicated absolute poverty nationwide, yet relative poverty remains a major governance challenge. Understanding public perceptions of poverty causes is important for refining national poverty alleviation strategies. Using data from the 2023 China National Survey of Public Welfare Attitudes ( N = 15,038), this study employs latent class analysis to identify four distinct attribution types among the Chinese public: internal, rejection, compound, and neutral. The compound attribution class accounts for the largest share, suggesting that poverty is most commonly understood as the combined outcome of individual capacities and structural constraints. Multinomial logistic regression further shows that attributions are shaped by both macro‐level determinants, such as region and residence, and micro‐level determinants, including self‐rated happiness, self‐rated life prospects, subjective social class, and socio‐demographic characteristics. These findings move beyond the conventional internal–external dichotomy and provide a multidimensional account of poverty attribution in China.