Heterogeneity and dynamics in network models
提出了一个允许经济网络连接存在异质性和动态性的空间建模框架，证明了模型的平稳性和遍历性，并应用于欧元区主权信用风险数据，发现考虑异质性和时变特征在样本内外都很重要。
Summary We propose an empirical spatial modeling framework that allows for both heterogeneity and dynamics in economic network connections. We establish the model's stationarity and ergodicity properties and show that the model's implied filter is invertible. While highly flexible, the model is straightforward to estimate by maximum likelihood. We apply the model to three datasets for Eurozone sovereign credit risk over the period Dec‐2009 to Dec‐2022. Accounting for both heterogeneity and time‐variation turns out to be empirically important both in‐sample and out‐of‐sample. The new model uncovers intuitive patterns that would go unnoticed in either homogeneous and/or static spatial financial network models.