Network dependence in multi-indexed data on international trade flows

Manfred M. Fischer, James P. LeSage

Publication: Working/Discussion PaperWU Working Paper

Abstract

Faced with the problem that conventional multidimensional fixed effects models only focus on unobserved heterogeneity, but ignore any potential cross-sectional dependence due to network interactions, we introduce a model of trade flows between countries over time that allows for network dependence in flows, based on sociocultural connectivity structures. We show that conventional multidimensional fixed effects model specifications exhibit cross-sectional dependence between countries that should be modeled to avoid simultaneity bias. Given that the source of network interaction is unknown, we propose a panel gravity model that examines multiplenetwork interaction structures, using Bayesian model probabilities to determine those most consistent with the sample data. This is accomplished with the use of computationally efficient Markov Chain Monte Carlo estimation methods that produce a Monte Carlo integration estimate of the log-marginal likelihood that can be used for model comparison. Application of the model to a panel of trade flows points to network spillover effects, suggesting the presence of network dependence and biased estimates from conventional trade flow specifications. The most important sources of network dependence were found to be membership in trade organizations, historical colonial ties, common currency, and spatial proximity of countries.
Original languageEnglish
Place of PublicationVienna
PublisherWU Vienna University of Economics and Business
DOIs
Publication statusPublished - 11 Sep 2020

Publication series

NameWorking Papers in Regional Science
No.2020/01

WU Working Paper Series

  • Working Papers in Regional Science

Cite this