国际小武器贸易模型的审查回归及其在探索未报告贸易方面的“法医”用途
Censored Regression for Modelling International Small Arms Trading and its "Forensic" Use for Exploring Unreported Trades
摘要：
在本文中，我们使用一个删失回归模型来调查挪威小武器转让倡议（NISAT）提供的小武器和弹药（SAA）的国际贸易数据。以网络为基础的观点来看，我们不仅依赖于外生协变量，但也估计内生网络效应。我们采用了空间自相关（SAR）模型与多个权重矩阵。采用蒙特卡罗期望最大化（MCEM）算法使可能性最大化。我们的方法揭示了强大而稳定的内生网络效应。此外，我们发现证据表明，民用和军用小武器出口之间存在着严重的路径依赖性和密切联系。然后以“法医”方式使用该模型分析潜在的网络结构，从而查明出口或进口趋势高于或低于数据所反映的趋势的国家。该方法也验证了使用模拟研究。
英文摘要：
In this paper we use a censored regression model to investigate data on the international trade of small arms and ammunition (SAA) provided by the Norwegian Initiative on Small Arms Transfers (NISAT). Taking a network based view on the transfers, we not only rely on exogenous covariates but also estimate endogenous network effects. We apply a spatial autocorrelation (SAR) model with multiple weight matrices. The likelihood is maximized employing the Monte Carlo Expectation Maximization (MCEM) 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
