  Motivated by a study of United Nations voting behaviors, we introduce a
regression model for a series of networks that are correlated over time. Our
model is a dynamic extension of the additive and multiplicative effects network
model (AMEN) of Hoff (2019). In addition to incorporating a temporal structure,
the model accommodates two types of missing data thus allows the size of the
network to vary over time. We demonstrate via simulations the necessity of
various components of the model. We apply the model to the United Nations
General Assembly voting data from 1983 to 2014 (Voeten (2013)) to answer
interesting research questions regarding international voting behaviors. In
addition to finding important factors that could explain the voting behaviors,
the model-estimated additive effects, multiplicative effects, and their
movements reveal meaningful foreign policy positions and alliances of various
countries.
