A DYNAMIC ADDITIVE AND MULTIPLICATIVE EFFECTS NETWORK MODEL WITH APPLICATION TO THE UNITED NATIONS VOTING BEHAVIORS

Bomin Kim, Xiaoyue Niu, David Hunter, Xun Cao

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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 (Statist. Sci. 36 (2021) 34–50). In addition to incorporating a temporal structure, the model accommodates two types of missing data and 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 (In Routledge Handbook of International Organization (2013) Routledge) 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.

Original languageEnglish (US)
Pages (from-to)3283-3299
Number of pages17
JournalAnnals of Applied Statistics
Volume17
Issue number4
DOIs
StatePublished - Dec 2023

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Statistics, Probability and Uncertainty

Cite this