The Determinants of Lifelong Learning in Europe

Alberto Costantiello (), Lucio Laureti and Angelo Leogrande

MPRA Paper from University Library of Munich, Germany

Abstract: The article affords the question of lifelong learning in Europe using data from the European Innovation Scoreboard-EIS in the period 2010-2019 for 36 countries. The econometric analysis is realized using WLS, Dynamic Panel, Pooled OLS, Panel Data with Fixed Effects and Random Effects. The results show that lifelong learning is, among other variables, positively associated to “Human Resources” and “Government procurement of advanced technology products” and is negatively associated, among others, to “Average annual GDP growth” and “Innovation Index”. A clusterization is realized using the k-Means algorithm with a confrontation between the Elbow Method and the Silhouette Coefficient. Subsequently, a Network Analysis was applied with the distance of Manhattan. The results show the presence of 4 complex and 2 simplified network structures. Finally, a comparison was made among eight machine learning algorithms for the prediction of the value of lifelong learning. The results show that the linear regression is the best predictor algorithm and that the level of lifelong learning is expected to growth on average by 1.12%.

Keywords: Innovation, and Invention: Processes and Incentives; Management of Technological Innovation and R&D; Diffusion Processes; Open Innovation. (search for similar items in EconPapers)
JEL-codes: O30 O31 O32 O33 O34 (search for similar items in EconPapers)
Date: 2022-08-07
New Economics Papers: this item is included in nep-big, nep-cse and nep-net
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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