USI CORe The Impact of the Geographical Dimension on ETER database: A First Exploratory Analysis Valerio Veglio; Università della Svizzera Italiana Benedetto Lepori; Università della Svizzera Italiana

USI Aim Preliminary descriptive analysis on the geographical structure of HEIs activities and the association with the FUAs characteristics.

USI European Tertiary Education Register (ETER)  ETER register provides a set of information including demographic information, geographical position (e.g.: latitude and longitude), number of students and degrees, number of staff, expenditures and revenues.  ETER database ( ): HEIs in 31 European Countries (all EU-28 countries expect Slovenia and Romania, plus Liechtenstein, Norway, Former Yugoslav Republic of Macedonia and Switzerland).  Lack of information on Academic Staff (FTE) for UK, France, Austria, Estonia, Greece, Latvia and Republic of Macedonia.

USI Match Definition  Match with the list of the municipalities  Match with ETER database in order to aggregate each FUAs with HEIs.

USI Research Methodology Data Sources  ETER Database  Organization for Economic Co-Operation and Development (OECD) Data Sample  110 Metropolitan FUAs for which OECD provides data Research Methods  Descriptive Analysis  Gini Index and/or Lorenz Curve  Kernell Density Function

USI ETER Variables (1/2) VariableMeasure Bachelor StudentsNumber of Students Enrolled at the Bachelor Level (ISCED 6) Master StudentsNumber of Students Enrolled at the Master Level (ISCED 7) Undergraduate StudentsTotal Number of Students Enrolled at the Diploma, Bachelor and Master Level (ISCED 5-7) Number of PhD StudentsNumber of PhD Students Enrolled (ISCED 8)

USI ETER Variables (2/2) Number of PubblicationsTotal Number of Publications in the Scimago Institutional Ranking EU-FP participationsNumber of Participations to EU-FPs from the EUPRO database Total Academic StaffFull Time Equivalent (FTE) Highest Degree DeliveredCategorical Variable: Diploma (0) – Bachelor (1) – Master (2) – PhD (3) Institution Category StandardizedCategorical Variables: Other Institutions (0) – University (1) – University of Applied Science (2) VariableMeasure

USI Functional Area Variables FU_CodeCode of the functional urban area FU_CoreCode, which shows that the HEI belong to the core of the municipalities. It is equal to 1 if the HEI refers to the core, 0 otherwise FU_NameName of the main city related to the functional urban area FU_RestrictedDummy variable. It identifies all geographical area with more than 500,000 inhabitants whereby the OECD provides statistics. Number of HEIsNumber of HEIs for each FUAs VariableMeasure

USI OECD Variables VariableMeasure PopulationTotal amount of the population for each functional area with more than 500,000 inhabitants. Gross Domestic Product (GDP)Total amount of the Gross Domestic Product for each functional area with more than 500,000 inhabitants. Patents ApplicationsTotal number of patents for each functional area with more than 500,000 inhabitants.

USI Descriptive Findings Total of Undergraduate StudentsTotal of PhD Students Metropolitan FUAs ETER Percentage Composition 52,36%62,40% Bivariate Correlations Total Population GDP_capita.352 ** EU_FP_capita-,097 Patents Application-,057 Total Academic Staff by TP-.270 * Total Undergraduate Students by TP-.210 * Total PhD Students by TP-,133 Number of Publications by TP-,142 Total Bachelor Students by TP-.205 * Total Master Students by TP-,143 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

USI Scatter Plot (1/2)

USI Scatter Plot (2/2)

USI Gini Index Values VariablesGini Index Value Patent Applications0,60 GDP_20100,51 Total Population 20120,44 Total Academic Staff FTE0,38 Total Undergraduate Students0,42 Total PhD Students0,47 EU-FPs Participations0,53 Number of Publications0,45 Total Bachelor Students0,42 Total Master Students0,49

USI Kernel Estimation Density

USI Discussion and Future Directions 1)Identification of Geographical Dimensions to be integrate in ETER database. 1)HEIs Geographic Analysis by Country (e.g.: Do most reputed HEIs are mainly concentrated in the core of the FUAs? Which most reputed HEIs belong to the periphery of the FUAs?). 3) Spatial Autoregressive Models. …

USI CORe Thank you for your attention!