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GTAP Resource #5323

"An integrated tool for GVCs analysis through the GTAP model"
by Antimiani, Alessandro, Ilaria Fusacchia and Luca Salvatici


Abstract
GCVs have become a key future of today's global economy and are the heart of international trade and investment policy. As over 50% of trade in goods takes place in intermediaries, planning a trade policy couldn’t rely upon gross trade statistics. New trade figures are required in order perform a more accurate analysis of trade via the deconstruction of traded products in terms of value-added content, distinguished by sector/region of origin/destination. Scientific efforts have been made in this direction, however, decompositions of gross trade are limited to descriptive statistics while many trade policy analysis are made by CGE models. The objective of this paper is to fill this gap, specifically for the GTAP model. In order to reckon with the structure in values in gross flows, we introduce in the model value-added multipliers, which combine the sectoral value-added shares in each country with the direct and indirect intermediate usage in the productive process. The condition that the sum over all sector/country sources in the value-added multipliers must give unity, assures that consistency is maintained. As a result, we obtain new variables –defined in terms of value added embedded in trade- to be analyzed in assessing the impact of counterfactual simulations using the GTAP model. Clearly, even without a simulation, the new code and routine introduced in the model also allow the analyst to use RunGTAP interface as tool to decompose gross trade flows.


Resource Details (Export Citation) GTAP Keywords
Category: 2017 Conference Paper
Status: Published
By/In: Presented at the 20th Annual Conference on Global Economic Analysis, West Lafayette, IN, USA
Date: 2017
Version:
Created: Fusacchia, I. (4/15/2017)
Updated: Fusacchia, I. (4/15/2017)
Visits: 2,332
- Baseline development
- Preferential trading arrangements
- The GTAP Data Base and extensions
- Not Applicable


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