For general panel data, by introducing network structure, network vector autoregressive (NVAR) model captured the linear inter dependencies among multiple time series. In this paper, we propose network vector autoregressive model for dyadic response variables (NVARD), which describes the dynamic process of dyadic data in the case of the dependencies among different pairs are taken into consideration. Besides, due to the existence of heterogeneity between time and individual, we propose time-varying coefficient network vector autoregressive model for dyadic response variables (VCNVARD). Finally, we apply these models to predict world bilateral trade flows.
翻译:就一般面板数据而言,通过引入网络结构,网络矢量自动递减(NVAR)模型捕捉了多种时间序列之间的线性相互依存关系。在本文件中,我们提议了dyadic反应变量(NVARD)的网络矢量自动递减模型,该模型说明在不同对子之间依赖关系的情况下,对dyadic数据的动态过程予以考虑。此外,由于时间和个人之间存在差异性,我们提议了dyadic反应变量(VCNVARD)的时等系数网络矢量自动递减模型。最后,我们将这些模型应用于预测世界双边贸易流量。