Cultural values vary significantly around the world. Despite a large heterogeneity, similarities across national cultures are to be expected. This paper studies cross-country culture heterogeneity via the joint inference of copula graphical models. To this end, a random graph generative model is introduced, with a latent space that embeds cultural relatedness across countries. Taking world-wide country-specific survey data as the primary source of information, the modelling framework allows to integrate external data, both at the level of cultural traits and of their interdependence. In this way, we are able to identify several dimensions of culture.

翻译：全球各地的文化价值观存在显著差异。尽管存在巨大的异质性，但国家文化之间的相似性也是可预期的。本文通过联合推断copula图形模型来研究跨国文化异质性。为此，我们引入了一种随机图生成模型，其潜空间嵌入了各国间的文化关联性。以全球特定国家调查数据为主要信息源，该建模框架能够在文化特征层面及其相互依存层面整合外部数据。通过这种方法，我们能够识别出多个文化维度。