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Gravity's Rainbow: A dynamic latent space model for the world trade network

Published online by Cambridge University Press:  15 April 2013

MICHAEL D. WARD ,
JOHN S. AHLQUIST  and
ARTURAS ROZENAS
MICHAEL D. WARD
Affiliation:
Department of Political Science, Duke University, Durham, NC 27708, USA (e-mail: michael.d.ward@duke.edu)
JOHN S. AHLQUIST
Affiliation:
Department of Political Science, University of Wisconsin, Madison, WI 53706, USA (e-mail: jahlquist@wisc.edu)
ARTURAS ROZENAS
Affiliation:
ISM University of Management and Economics, Vilnius, Lithuania (e-mail: arturasro@gmail.com)
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Abstract

The gravity model, long the empirical workhorse for modeling international trade, ignores network dependencies in bilateral trade data, instead assuming that dyadic trade is independent, conditional on a hierarchy of covariates over country, time, and dyad. We argue that there are theoretical as well as empirical reasons to expect network dependencies in international trade. Consequently, standard gravity models are empirically inadequate. We combine a gravity model specification with “latent space” networks to develop a dynamic mixture model for real-valued directed graphs. The model simultaneously incorporates network dependencies in both trade incidence and trade volumes. We estimate this model using bilateral trade data from 1990 to 2008. The model substantially outperforms standard accounts in terms of both in- and out-of-sample predictive heuristics. We illustrate the model's usefulness by tracking trading propensities between the USA and China.

Keywords

gravity modeltradenetworkslatent space

Information

Type
Research Article
Information
Network Science , Volume 1 , Issue 1 , April 2013 , pp. 95 - 118
Copyright
Copyright © Cambridge University Press 2013

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