In this paper, we use a censored regression model to investigate data on the international trade of small arms and ammunition provided by the Norwegian Initiative on Small Arms Transfers. Taking a network-based view on the transfers, we do not only rely on exogenous covariates but also estimate endogenous network effects. We apply a spatial autocorrelation gravity model with multiple weight matrices. The likelihood is maximized employing the Monte Carlo expectation maximization algorithm. Our approach reveals strong and stable endogenous network effects. Furthermore, we find evidence for a substantial path dependence as well as a close connection between exports of civilian and military small arms. The model is then used in a ‘forensic’ manner to analyse latent network structures and thereby to identify countries with higher or lower tendency to export or import than reflected in the data. The approach is also validated using a simulation study.

中文翻译：

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用于建模小武器贸易量的截尾回归及其用于探索未报告贸易的“法证”用途

在本文中，我们使用删失回归模型来调查挪威小武器转让倡议提供的小武器和弹药国际贸易数据。从基于网络的角度来看，我们不仅依赖于外生协变量，而且还估计了内生网络效应。我们应用具有多个权重矩阵的空间自相关重力模型。使用蒙特卡罗期望最大化算法最大化似然。我们的方法揭示了强大而稳定的内生网络效应。此外，我们发现了大量路径依赖的证据，以及民用和军用小武器出口之间的密切联系。然后以“取证”方式使用该模型来分析潜在的网络结构，从而确定出口或进口趋势高于或低于数据所反映的国家。该方法还使用模拟研究进行了验证。