How geographical distance, GDP and linguistic affinity affects portuguese exports? A multimensional approach from 2011 to 2015

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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Detalhes bibliográficos
Autor principal: Ribeiro, Sandra (author)
Outros Autores: Santos, António Duarte (author), Castela, Guilherme (author), Silva, Nelson Tavares da (author)
Formato: conferenceObject
Idioma:eng
Publicado em: 2017
Assuntos:
Texto completo:http://hdl.handle.net/11144/3142
País:Portugal
Oai:oai:repositorio.ual.pt:11144/3142
Descrição
Resumo: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 exports for these countries, (b) the changes between 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 positive relationship. In the other hand, there were identified three clusters of countries for which Portugal had different export performances, influenced, taking into account distance, linguistic affinity and GDP. 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.