英文标题：
《Enhanced Gravity Model of trade: reconciling macroeconomic and network
  models》
---
作者：
Assaf Almog, Rhys Bird, Diego Garlaschelli
---
最新提交年份：
2019
---
英文摘要：
  The structure of the International Trade Network (ITN), whose nodes and links represent world countries and their trade relations respectively, affects key economic processes worldwide, including globalization, economic integration, industrial production, and the propagation of shocks and instabilities. Characterizing the ITN via a simple yet accurate model is an open problem. The traditional Gravity Model (GM) successfully reproduces the volume of trade between connected countries, using macroeconomic properties such as GDP, geographic distance, and possibly other factors. However, it predicts a network with complete or homogeneous topology, thus failing to reproduce the highly heterogeneous structure of the ITN. On the other hand, recent maximum-entropy network models successfully reproduce the complex topology of the ITN, but provide no information about trade volumes. Here we integrate these two currently incompatible approaches via the introduction of an Enhanced Gravity Model (EGM) of trade. The EGM is the simplest model combining the GM with the network approach within a maximum-entropy framework. Via a unified and principled mechanism that is transparent enough to be generalized to any economic network, the EGM provides a new econometric framework wherein trade probabilities and trade volumes can be separately controlled by any combination of dyadic and country-specific macroeconomic variables. The model successfully reproduces both the global topology and the local link weights of the ITN, parsimoniously reconciling the conflicting approaches. It also indicates that the probability that any two countries trade a certain volume should follow a geometric or exponential distribution with an additional point mass at zero volume.
---
中文摘要：
国际贸易网络（ITN）的节点和链接分别代表世界各国及其贸易关系，其结构影响着世界各地的关键经济进程，包括全球化、经济一体化、工业生产以及冲击和不稳定的传播。通过一个简单但准确的模型来描述ITN是一个开放的问题。传统的引力模型（GM）利用GDP、地理距离等宏观经济属性，以及可能的其他因素，成功地再现了联系国之间的贸易量。然而，它预测的网络具有完整或同质的拓扑结构，因此无法重现ITN的高度异构结构。另一方面，最近的最大熵网络模型成功地再现了ITN的复杂拓扑结构，但没有提供有关贸易量的信息。在这里，我们通过引入贸易的增强重力模型（EGM）来整合这两种目前不兼容的方法。EGM是最大熵框架下将GM与网络方法相结合的最简单模型。通过一个透明到足以推广到任何经济网络的统一和原则性机制，专家组提供了一个新的计量经济学框架，其中贸易概率和贸易量可以由二元和国别宏观经济变量的任何组合单独控制。该模型成功地再现了ITN的全局拓扑结构和局部链路权重，节省了相互冲突的方法。它还表明，任何两个国家进行某一交易量的概率应遵循几何或指数分布，且在零交易量下有一个额外的点质量。
---
分类信息：

一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
--
一级分类：Physics        物理学
二级分类：Disordered Systems and Neural Networks        无序系统与神经网络
分类描述：Glasses and spin glasses; properties of random, aperiodic and quasiperiodic systems; transport in disordered media; localization; phenomena mediated by defects and disorder; neural networks
眼镜和旋转眼镜；随机、非周期和准周期系统的性质；无序介质中的传输；本地化；由缺陷和无序介导的现象；神经网络
--
一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
--

---
PDF下载：
-->