Randomization Tests for Equality in Dependence Structure
提出一种新的统计检验方法，通过比较两组数据的整个依赖函数（copula）而非单一指标，判断其依赖结构是否相同。该方法无需调参，小样本下表现优异，并应用于收入与消费依赖关系及英国脱欧对欧洲金融市场整合影响的分析。
We develop a new statistical procedure to test whether the dependence structure is identical between two groups. Rather than relying on a single index such as Pearson’s correlation coefficient or Kendall’s <i>τ</i>, we consider the entire dependence structure by investigating the dependence functions (copulas). The critical values are obtained by a modified randomization procedure designed to exploit asymptotic group invariance conditions. Implementation of the test is intuitive and simple, and does not require any specification of a tuning parameter or weight function. At the same time, the test exhibits excellent finite sample performance, with the null rejection rates almost equal to the nominal level even when the sample size is extremely small. Two empirical applications concerning the dependence between income and consumption, and the Brexit effect on European financial market integration are provided.