The Drivers of National System of Innovation in Portugal: A Panel Data Analysis
Marcelo Duarte 1 * , Fernando Carvalho 1
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1 University of Coimbra, CeBER, Faculty of Economics, PORTUGAL
* Corresponding Author

Abstract

The growing awareness of the importance of national systems of innovation on countries’ development led to an increased availability of instruments designed to measure and compare the innovative capacity of countries. Such instruments provide policymakers with a panoply of relevant information, with which they can stimulate innovation within their territory, thereby increasing national competitiveness. Among the most used innovation indices, the Global Innovation Index (GII) stands out by explicitly distinguishing innovation inputs and outputs, hence, drawing from its input-output framework and extant literature on innovation, we intend to answer the question: Which innovation inputs are more strongly related to innovative outputs? Thus, deriving policy implications aimed at improving Portugal’s innovative readiness. To answer this question, and due to the cross-sectional nature of the GII, we have developed our own panel dataset version composed by 92 countries in the period 2013-2018, which we then analyse through a series of multiple regression techniques, emphasising the results of Eurozone countries and comparing Portugal to them. Results suggest a strong, positive influence of Business Sophistication on innovation outputs in Eurozone countries, derived mainly from the capacity of domestic firms to absorb knowledge. Possible policy implications are derived from this fact, such as, for instance, an encouragement to inward foreign direct investment. However, further research is needed to analyse the differentiated effects of such encouragement, as well as for other surprising results of our study.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

https://doi.org/10.29333/jisem/8248

J INFORM SYSTEMS ENG, 2020 - Volume 5 Issue 2, Article No: em0114

Publication date: 08 May 2020

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Article Downloads: 83

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