In this article we investigate the determinants of “New Doctorate Graduates” in Europe. We usedatafrom the EIS-European Innovation Scoreboard of the European Commission for 36 countries in theperiod 2010-2019 with Pooled OLS, Dynamic Panel, WLS, Panel Data with Fixed Effects and PanelData with Random Effects. We found that “New Doctorate Graduates” is positively associated, amongothers, with “Human Resources” and “Government Procurement of Advanced Technology Products”and negatively, associated among others, with “Total Entrepreneurial Activity” and“Innovation Index”.We apply a clusterization with k-Means algorithm either with the Silhouette Coefficient either with theElbow Method and we found that in both cases the optimal number of clusters is three. Furthermore, weuse the Network Analysis with the Distance of Manhattan, and we find the presence of seven networkstructures. Finally, we propose a confrontation among ten machine learning algorithms to predict thevalue of “New Doctorate Graduates” either with Original Data-OD either with Augmented Data-AD.Results show that SGD-Stochastic Gradient Descendent is the best predictor for OD while LinearRegression performs better for AD (PDF) The Impact of New Doctorate Graduates on Innovation Systems in Europe. Available from: https://www.researchgate.net/publication/380315490_The_Impact_of_New_Doctorate_Graduates_on_Innovation_Systems_in_Europe [accessed May 07 2024].
The Impact of New Doctorate Graduates on Innovation Systems in Europe
Alberto Costantiello
;Fabio Anobile
;Lucio Laureti
;
2024-01-01
Abstract
In this article we investigate the determinants of “New Doctorate Graduates” in Europe. We usedatafrom the EIS-European Innovation Scoreboard of the European Commission for 36 countries in theperiod 2010-2019 with Pooled OLS, Dynamic Panel, WLS, Panel Data with Fixed Effects and PanelData with Random Effects. We found that “New Doctorate Graduates” is positively associated, amongothers, with “Human Resources” and “Government Procurement of Advanced Technology Products”and negatively, associated among others, with “Total Entrepreneurial Activity” and“Innovation Index”.We apply a clusterization with k-Means algorithm either with the Silhouette Coefficient either with theElbow Method and we found that in both cases the optimal number of clusters is three. Furthermore, weuse the Network Analysis with the Distance of Manhattan, and we find the presence of seven networkstructures. Finally, we propose a confrontation among ten machine learning algorithms to predict thevalue of “New Doctorate Graduates” either with Original Data-OD either with Augmented Data-AD.Results show that SGD-Stochastic Gradient Descendent is the best predictor for OD while LinearRegression performs better for AD (PDF) The Impact of New Doctorate Graduates on Innovation Systems in Europe. Available from: https://www.researchgate.net/publication/380315490_The_Impact_of_New_Doctorate_Graduates_on_Innovation_Systems_in_Europe [accessed May 07 2024].I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
