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Econometrics 2018, 6(1), 9; https://doi.org/10.3390/econometrics6010009

A Spatial-Filtering Zero-Inflated Approach to the Estimation of the Gravity Model of Trade

1
Department of Economics and Management, University of Brescia, 25122 Brescia, Italy
2
Department of Economics, University of Bologna, 40126 Bologna, Italy
3
The Rimini Centre for Economic Analysis (RCEA), Waterloo, ON N2L3C5, Canada
4
School of Economic, Political & Policy Sciences, The University of Texas at Dallas, Richardson, TX 75080, USA
*
Author to whom correspondence should be addressed.
Received: 23 September 2016 / Revised: 10 January 2018 / Accepted: 12 February 2018 / Published: 22 February 2018
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Abstract

Nonlinear estimation of the gravity model with Poisson-type regression methods has become popular for modelling international trade flows, because it permits a better accounting for zero flows and extreme values in the distribution tail. Nevertheless, as trade flows are not independent from each other due to spatial and network autocorrelation, these methods may lead to biased parameter estimates. To overcome this problem, eigenvector spatial filtering (ESF) variants of the Poisson/negative binomial specifications have been proposed in the literature on gravity modelling of trade. However, no specific treatment has been developed for cases in which many zero flows are present. This paper contributes to the literature in two ways. First, by employing a stepwise selection criterion for spatial filters that is based on robust (sandwich) p-values and does not require likelihood-based indicators. In this respect, we develop an ad hoc backward stepwise function in R. Second, using this function, we select a reduced set of spatial filters that properly accounts for importer-side and exporter-side specific spatial effects, as well as network effects, both at the count and the logit processes of zero-inflated methods. Applying this estimation strategy to a cross-section of bilateral trade flows between a set of 64 countries for the year 2000, we find that our specification outperforms the benchmark models in terms of model fitting, both considering the AIC and in predicting zero (and small) flows. View Full-Text
Keywords: bilateral trade; unconstrained gravity model; eigenvector spatial filtering; zero flows; backward stepwise; zero-inflation bilateral trade; unconstrained gravity model; eigenvector spatial filtering; zero flows; backward stepwise; zero-inflation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Metulini, R.; Patuelli, R.; Griffith, D.A. A Spatial-Filtering Zero-Inflated Approach to the Estimation of the Gravity Model of Trade. Econometrics 2018, 6, 9.

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