MCMC estimation of panel gravity models in the presence of network dependence
James LeSage () and
Manfred Fischer ()
No 2018/07, Working Papers in Regional Science from WU Vienna University of Economics and Business
Past focus in the panel gravity literature has been on multidimensional fixed effects specifications in an effort to accommodate heterogeneity. After introducing fixed effects for each origin- destination dyad and time-period speciffic 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 MCMC 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.
Keywords: origin-destination panel data flows; cross-sectional dependence; log-marginal likelihood; sociocultural distance; convex combinations of interaction matrices (search for similar items in EconPapers)
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