The Network of Foreign Direct Investment Flows: Theory and Empirical Analysis

Schoeneman, John; Zhu, Boliang; Desmarais, Bruce A.

doi:10.2139/ssrn.3018031

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Valued Network Models and Zero-inflated Data1

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“…Even in the years with the highest density, we have roughly 98% zeros in the data, excluding the possibility to use a GERGM. As indicated also in Schoeneman et al (2017), the GERGM model cannot handle zero-inflated data.…”

Section: Valued Network Models and Zero-inflated Datamentioning

confidence: 98%

Exploring dependence structures in the international arms trade network: A network autocorrelation approach

Lebacher

Thurner

Kauermann

2019

Statistical Modelling

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In the paper we analyse dependence structures among international trade flows of major conventional weapons from 1952 to 2016. We employ a Network Disturbance Model commonly used in inferential network analysis and spatial econometrics. The dependence structure is represented by pre-defined weight matrices that allow for relating the arms trade flows from the network of international arms exchange. Several different weight matrices are compared by means of the AIC in order to select the best dependence structure. It turns out that the dependence structure among the arms trade flows is rather complex and can be represented by a specification that, simply speaking, relates each arms trade flow to all exports and imports of the sending and the receiving state. By controlling for explanatory variables we are able to show the influence of political and economic variables on the volume traded.

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Section: Valued Network Models and Zero-inflated Datamentioning

confidence: 98%