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Estimating International Trade Margins Shares by Mode of Transport for the GTAP Data Base

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  • Jose Nuno-Ledesma
  • Nelson B. Villoria

Abstract

We estimate international transportation margin shares by mode of transport for the Global Trade Analysis Project (GTAP) Data Base. For each available origin-destination-GTAP sector triplet, we estimate the fractional share of the transport margin attributable to air, water, and other shipping modes. We use published relationships between ad valorem proportional changes in prices due to transportation costs and distances, weight-value ratios and fuel prices. Our final database contains 344,554 observations (origin-destination-sector-mode combinations) with transportation margin modal shares organized by 228 exporter countries, 209 importer countries, 45 traded GTAP sectors and 3 transportation modes. The main contribution of this article is to bring a more comprehensive set of information on trade by transport mode covering around 65% of global trade in 2004 and 55% in 2011. Our estimated shares contrast with those traditionally used in the GTAP Data Base which are extrapolations based solely on the modes of transport used by US exporters. A comparison of our shares with those used in version 9.0 of the GTAP Data Base reveals that the role of water transportation services in international trade is underestimated, while that of air transportation is overestimated. Overall, we find that estimations using the modal shares in version 9.0 of the GTAP Data Base overestimate the greenhouse gas emissions associated with international transport. Our new data were used to estimate transport margins by mode in Version 9.1 of the GTAP Data Base, and it is expected that our methods will be used to update future versions of the database.

Suggested Citation

  • Jose Nuno-Ledesma & Nelson B. Villoria, 2019. "Estimating International Trade Margins Shares by Mode of Transport for the GTAP Data Base," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 4(1), pages 28-49, June.
    • Handle: RePEc:gta:jnlgea:v:4:y:2019:i:1:p:28-49
    DOI: http://dx.doi.org/10.21642/JGEA.040102AF
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