Portuguese exports and its relations with geographical distance, gross domestic product and linguistic affinity a biplot approach

The geographical scope and the consequent reduction in transport costs, the evolution of the GDP of the destination countries, the membership to the European Union and linguistic affinity are use as support to an explanatory gravitational perspective for Portuguese exports in 2011-2015. This was don...

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Bibliographic Details
Main Author: Santos, António Duarte (author)
Other Authors: Ribeiro, Sandra (author), Castela, Guilherme (author), Silva, Nelson (author)
Format: article
Language:eng
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/11144/3847
Country:Portugal
Oai:oai:repositorio.ual.pt:11144/3847
Description
Summary:The geographical scope and the consequent reduction in transport costs, the evolution of the GDP of the destination countries, the membership to the European Union and linguistic affinity are use as support to an explanatory gravitational perspective for Portuguese exports in 2011-2015. This was done for the 61 main trading partners of Portugal’s exports of goods and services over the period 2011-2015, with a multidimensional perspective, using the HJ-BIPLOT method developed by Galindo (1986). This methodological approach identified and categorized the sample countries in latent constructs of reduced dimensionality related to the exports policy. The simultaneous factorial representation identified (a) the most relevant variables to characterize Portugal main export destination countries, (b) the changes that occurred during the period in analysis, and (c) the relations between variables, between countries, and between variables and countries. This approach showed that distance is not a main determinant for exports, and that GDP and export volumes have a slightly positive relationship. In the other hand, there were identified four clusters of countries, via two step algorithm (Chiu et al. 2001), for which Portugal had different performances, taking into account not only exports, distance, and GDP but also linguistic affinity and EU membership. This analysis showed to be useful in export problematic research, when studying multivariate data and also, by its visual nature, a potential tool for producing richer information for the academia and also for international trade policy makers.