Conventional versus network dependence panel data gravity model specifications

Past focus in the panel gravity literature has been on multidimensional fixed effects specifications
in an effort to accommodate heterogeneity. After introducing conventional multidimensional fixed effects, we find evidence of cross-sectional dependence in
flows.
We propose a simultaneous dependence gravity model that allows for network dependence
in flows, along with computationally efficient Markov Chain Monte Carlo estimation methods
that produce a Monte Carlo integration estimate of log-marginal likelihood useful 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.