A Gravity Model Analysis of Portuguese Foreign Direct Investment

• Autor(a) principal: Leitão, Nuno Carlos
• Data de Publicação: 2023
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.15/4554
• topic: Foreign direct investment; Gravity model; Panel data

Cultural and linguistic affinities have been studied in international business through the gravity model and economics of language. International investment theories enable the assessment of organisational, location, and internalisation motivations. The present study assesses the impact of transport costs, common language and market size based on the arguments of the gravity model, economics of language, and international investment theory. This investigation evaluates the relationship between the Portuguese FDI and the gravity model, using panel data between 2005 and 2020. The OLS estimator, PPML-Poisson Pseudo-Maximum-Likelihood estimator, and panel quantile regressions were used as an econometric methodology. Regarding research, we sought to understand to what extent cultural and linguistic issues, namely Portuguese-speaking countries, contribute to explaining Portuguese FDI. The economic dimension of the Portuguese economy and investor countries were introduced into the regression model. In addition, transportation and transaction costs were analysed across geographical distances. The econometric results show that the common language and cultural aspects are positively correlated with the Portuguese FDI, which allows us to conclude that the Portuguese language reduces the asymmetries between the home market and the host country. When panel quantile regressions are applied, it is possible to observe that the Portuguese economy has dimension enough to attract FDI, just as the countries investing in the Portuguese economy have a return on the investment made. Finally, geographical distance negatively impacts FDI, showing that geographical proximity increases the probability of attracting FDI.