Testing for Convergence Clubs in Income Per Capita: A Predictive Density Approach*
提出一种基于预测密度的技术，用于联合检验面板中未知大小的分组并估计各组参数，应用于识别欧洲区域和OECD国家人均收入的趋同俱乐部。
The article proposes a technique, based on the predictive density of the data, conditional on the parameters of the model, to jointly tests for groups of unknown size in a panel and to estimate the parameters of each group. The procedure is applied to the problem of identifying convergence clubs in scaled income per capita data. The steady‐state distribution of European regional data clusters around four poles of attraction with different economic features. The distribution of income per capita of OECD countries has two poles of attraction and each group clearly identifiable economic characteristics. We share the uncommonness of being different. J. P. Roche