Assessing Bipolarization: A Consistent Nonparametric Test for Relative Bipolarization Lorenz Dominance
提出一个一致非参数检验，用于检测相对两极分化洛伦兹支配，能捕捉传统不平等指标遗漏的“中产阶级空心化”现象，并应用于中国家庭面板数据，评估精准扶贫政策效果。
ABSTRACT This study introduces a consistent nonparametric test for Relative Bipolarization Lorenz Dominance (RBLD), addressing a methodological gap wherein the Relative Bipolarization Location Curve (RBLC) criterion lacked a robust statistical implementation. We develop a consistent nonparametric test for RBLD that is asymptotically valid. Simulation results demonstrate its superior power in detecting “middle‐class hollowing”, a structural shift often missed by traditional inequality metrics. We apply this test to China Family Panel Studies (CFPS) data (2012–2020) and find two key results: (1) our cross‐sectional analysis reveals a clear hierarchy of regional household consumption bipolarization where traditional LD tests are inconclusive; and (2) a dynamic evaluation of the Targeted Poverty Alleviation (TPA) policy using Panel Data (PD) sampling reveals a successful post‐2016 reversal of worsening bipolarization, but an ultimately incomplete recovery for the most vulnerable regions. Our test thus provides a new diagnostic tool for a post‐poverty‐alleviation era focused on structural disparity.