Italian Universities : Institutional Mandate and Communitarian Engagement

To make their mandate more efficient, universities have to either offer services to students either produce innovation and scientific research. From this point of view it is difficult for universities to focus their attention on economic and financial performance. Instead, it is much more relevant for the university to find models of governance that are able to bring together profitability, financial sustainability, and social and communitarian commitment. Universities generate knowledge that can be used to improve the standard of economic and social life in the territorial environment. For these reasons it is important to analyze relations between university and community of reference. We found that italian universities that perform better are associated with communities able to generate individual and social welfare. Better universities have also more active and skilled student populations. Monthly data are considered for the period 2012 and 2017 for 58 italian universities. Data are collected from BESISTAT, Almalaurea and Center for World University Rankings-CWUR. The complex database has been realized by using KNIME mixing different sources in an original metric environment. We use panel data approach to estimate the level of italian ranking in CWUR statistics by the usage two different sets of variables: BES-ISTAT and SIOPE. The increasing in the Global International Ranking can be realized either directly by increasing the level of services and products generates, either indirectly improving the spillovers effect of universities in respect to a certain community of reference.


Introduction
Universities are called to play an international role in the global competitive challenge (Shin, 2012). However, not all universities are prepared for this global challenge. In fact, the italian university model seems is chracterized by a twofold dilemma: on the one hand universities lack financial resources (Agasisti & Salerno, Assessing the cost efficiency of Italian universities, 2007), on the other hand universities suffer for an inefficiency in resource management. The two elements toghether define a decline in the italian universities that is evident in the Global Universities Ranking. One of the problems of the italian universities is based on the question of multi-objective. In effect universities have a multiobjective managerial model that is able to put toghether financial performance, educational objectives and social and communitarian commitment. University are also involved in realizing a stakeholder-oriented governance (Wise, Dickinson, Katan, & Gallegos, 2018). This dual condition involves a reduction in the competitive capacity of the university body which is further complicate by the fact that it has a substantially multi-objective mandate (Piattoni, 2009). In fact, the aims of the university body are of various kinds, on the one hand, in fact, there are the traditional didactic and scientific research objectives, on the other hand there are, on the other hand, purposes of a further nature, which have been added to the performance of the academic activity, and which are essentially made up of spillovers towards local businesses in the sense of productive collaborations (Ciuchta, Gong, Miner, Letwin, & Sadler, 2016) of knowledge, innovation, human capital and patenting (Toole, Czarnitzki, & Rammer, 2015).
The role of universities has greatly increased. In fact, university bodies have increasingly become organizations with a substantially multi-objective character. However, this multi-objective condition has effectively modified and stressed the same university organizational structure that often lacks the financial, technological and human capital resources to be able to achieve the goals set by the legislator, chosen by university governance or explicitly requested by the stakeholders and constituencies of reference. The role of universities is therefore very varied. Clearly the size of the international competition operates within the various fields of activity and entails for the universities the need to be effectively productive both in teaching and in research (Harland, 2016) and also in the activities of strengthening the industrial, productive and institutional reference system. The possibility for the university to correspond to those that are multi-objective structures is essential also because indeed among the various activities carried out by the university there are virtuous relationships, or as a sort of "Inner spillovers" that are produced in the bringing together training, research and orientation (Tight, 2016) towards strengthening the entrepreneurial and institutional territorial system. In fact, many universities place themselves as tools for strengthening business activity (Rampersad, 2015), or rather as tools that can actually be able to guide the economic system towards productivity growth. Universities are involved in the attempt to change the cultural and social system through the development of new businesses and technologies. The universities then deal with both producing a new human capital that can be used within the context of the labor market considered, and also have the capacity to produce technologies, that is, the knowledge applied to high innovative content that are able to generate income, value added, increased productivity, and strengthening the company's competitiveness. University actively participate to regional development (Boucher, Conway, & Van Der Meer, 2003). However, it is also necessary to consider the role of the engagement of the reference communities (Weerts & Sandmann, 2010). That is the territories within which the university structures insist must be involved, or actively participate, in the processes of scientific, cultural and technological empowerment produced by the universities (Bringle & Hatcher, 2002). This creates an important spillover relationship between the university body and the local reference market that constitutes an essential dimension of the complex system of value-added creation within the economy and the knowledge society (Fitzgerald, Bruns, Sonka, Furco, & Swanson, 2016). In this sense the university produces and requires a certain cultural climate with respect to which there is evidently a certain endogenous relationship: that is, on the one hand the university has an impact on the productive realities through the determination of market outputs, while on the other hand, obviously, a production and growth-oriented society necessarily produces human capital that is more oriented both to attend the university and to actively participate through the engagement processes within the civilization project proposed by the university body (Ostrander, 2004). It is therefore very probable for example that the territorial economies characterized by a high added value also have an evolved and competitive international university system, while, on the contrary, the territories in which economic development is low have non efficient competitive international universities.
In particular we can analyze the complex set of rules and constraints that guide university governance. In particular there are 4 kind of dependent variables to explain the institutional constraints of the university i.e.:  Law University Order Regulations: these are laws enforced at a State-level to determine what are the main objectives of universities. Laws are devoted to delimitate the role of universities either on a financial point of view either in the sense of global and social outputs.
 Ministerial Regulations: these are regulation generated at a governative level.
 University Statues: indipendent statues autonomously predisposed by universities;  Private Bargaining: private contracts that are determined between private firms, public institutions and universities.
The relation among variables is indicated in the sequent formula: The complex set of Institutional Constraints is able to determine a certain number of limitation in respect to the ability of the university to generate valuable objective. Institutional constraints define the university governance. In particular universities should promote policies such as dialogue, integration, social and communitarian commitment, and should create a opportunies to improve the level of institutional performance and the degree of innovation and reasearch. Universities have to realize a multi-objective productivity function generating not only education and knowledge for students but also creating the conditions for a social, economic, institutional and enterpreneurial improvements (Christensen, 2011). In this sense it is very important to analyze what are the possibilities for the universities to improve private bargaining and university statues to increase the relationships among multiple stakeholders. In this sense, even if universities have to respect some kind of financial constraints they also have to realize a sort of stakeholder governance oriented model in which universities try to maximize the production function of constituencies and communities (Stanton, 2008). It is clear that the application of a stakeholder governance model for universities is important and crucial to correspond to the multiple objective function of the universities. For example in the case of a multiple stakeholder governance model for universities it is possible to maximize in the same set of choices either the position of students, either the position of lenders, the position of communities and societies that are both internal and external in respect to the governance model (Amaral & Magalhaes, 2002). The multi-stakeholder model has the ability to help the universities either in the sense of governance and management either in the sense of empowerment, engagement with respect to communities generating deep and productive social relations (Miller, McAdam, & McAdam, 2014).
In our research we analyze two different models to estimate the role of Italian Universities in the Global Universities ranking. The independent variable is both the model is the same i.e. the rank of italian Universities in the Global University Ranking. But dependent variables are different in both the models. In the first model a set of 11 BES-ISTAT dependent variables are regressed on the independent variable; in the second model a set of 22 Almalaurea dependent variables are regressed on the independent variable. Data in both cases are referred to 59 universities based on the italian territory and collected on a montlhy based between 2012 and 2017.
In particular we argue that universities face an international and national competition (Cattaneo, Malighetti, Meoli, & Paleari, 2017). Italian universities in particular suffer for a twofold problem: on the one hand they have low financial resources, on the other hand they show inefficiency in the management of existing resources (Bini & Masserini, 2016). Our hypothesis is that not only universities are associated with the presence of more developed communities and, reversely, developed communities have the ability to promote internationally well-ranked universities (Shiel, Leal Filho, do Paço, & Brandli, 2016). This means that there is a bijective relation between communities and universities: performative universities promote developed communities and developed communities are associated to the presence of performative universities in the sense of global ranking (Hart, Gerhardt, & Rodriguez, 2009). To make their mandate more efficient, universities have to either offer services to students either produce innovation and scientific research. From this point of view, it is difficult for universities to focus their attention on economic and financial performance. Instead, it is much more relevant for the university to find models of governance that are able to bring together profitability, financial sustainability, and social and communitarian commitment (Gilchrist, 2019). Universities have financial and statutory constraints (Agasisti, Catalano, Di Carlo, & Erbacci, 2015). They have also to produce innovation and research that can produce value for communities and firms (Amador, Pérez, López-Huertas, & Font, 2018). Universities generates knowldge that can be used to improve the standard of economic and social life in the territorial environment (Audretsch, Lehmann, & Warning, 2017). For these reasons it is important to analyze relations between university and community of reference (Brennan, Cochrane, Lebeau, & Williams, 2018). We found that italian universities that perform better are associated with communities oriented to generate individual and social welfare.
Better universities have also more active and skilled student populations.
To analyze this topic we use monthly data collected during the period 2012-2017 for 58 italian universities. The merge of these different database is realized using KNIME.
Methodologically we analyze two different kind of models: the first model is devoted to estimate the impact of BES-ISTAT (Istat, 2019) variables on the CWUR dataset; the second model describe how changes in composition of student population as indicated in Almalaurea database is associated to CWUR rankings. Interesting conclusion are realized showing that universities, evaluated in the sense of CWUR, prosper in connection with the presence of communities with good performance in the sense of ISTAT-BES and in connection with well-educated and prosperous student population. Such considerations let us infer the presence of a dualistic and reverse proposition in which not only universities generate good communities and well-educated and proactive student population, but also good communities and active student population are associated to more performative universities. Data are elaborated using OLS, panel data with fixed effects, random effect and using principal component analysis.
We conclude good communities in the sense of ISTAT-BES and the presence of a good quality of student population are associated to universities with good international rankings. We estimate two different kind of models one able to shed light on the socio-economic condition of the communities and the other able to shed light on the relations between the world university score and the characteristics of the student population.

Causality, Causation and Regressions
Good universities are positively associated to high opulent economies and to affluent society (Mueller, 2006). But it is questionable if good universities generate opulent economies and affluent society or if opulent economies and affluent society generate good universities (Hausman, 2012). We should exclude the presence of cause-effect nexus between the presence of universities and the presence of opulent and affluent societies. The causality effect should be rejected. It's more useful referring to the association of different phenomena. We are not able to say if universities generate affluent societies or if affluent societies generate good universities. We can only say that either good universities and affluent societies are related and associated in a unified communitarian context. The rejection of the cause-effect nexus is based on the presence of logical and methodological limitations in respect to the presence of multiple analysis.
Causality, causation, correlation and regressions. Only a limited set of correlation can be considered as based on causation. In particular the causation effect is based on the possibility to affirm that a single cause generates a certain set of effects while correlations are simply devoted to indicate the presence of a certain set of relation among different categories. The correspondence between causation and correlation is limited.

Figure 1. The relations between causality, causation, correlation and regressions.
Causality can be considered as a general that adfirm the presence of cause-effect nexus. While, on the other side causation is a strong definition of causality in which a certain cause define a limited set of effects. But even if it possible to adfirm that regressions, and correlations are able to illuminate a certain degree of causation is not possible to prove metrically the causation effects. The idea of causality has been introduced in the econometric framework through the idea of Granger causality (Granger, 1988) in time series modeling. In particular Granger causality asserts that if there is causality between two different variables than the prediction of a single variable using both variables performs better than the prediction of the single variable using only one time series. Then it is possible to assert than between the two variables there is a causality in the sense of Granger. But Granger causality is only a formal definition of causality. There are many critiques in the usage of strong causality in the context of social sciences (Rein & Winship, 1999).
In fact, the presence of causality in the socio-economic context remains effectively a remote possibility due to the presence of endogeneity. Socio-economic variables in fact are characterized by strong endogeneity. The presence of endogeneity in the economic context has generated relevant theories such as for example in the case of theory of endogeneous growth. Due to the presence of strong endogeneity it is difficult to analyze the presence of causality. In this sense it is important to distinguish between causality and causation.
In particular causation (Philosophy, The Metaphisics of causation, 2003) can be considered as a strong definition of casuality. Causation asserts that the presence of a certain effect is due to a certain cause. It is not possible to exclude the existence of a causation effects in the presence either of endogeneity or exogeneity. The absence of causation does not mean that correlations don't apply (Philosophy, Aristotle on Causality, 2019). In effect while causation is rare and difficult to prove and justify, correlation and mere relations, that are approximations of causality, can be found easily and used to justify complex economic models.
We have to analyze the multiple relation between endogeneity, exogeneity, causation and a-causation. In particular we can say that the econometric techniques are not able to determinate with a high degree of certainty the presence of causation in endogenous and exogenous models. Econometric techniques are only able to adfirm that some variables are related or co-related with others. In the case of endogenous models the correlation or regressions are all determined inside the economic modeling, while in the case of exogenous models the correlations and regressions are determined in the connection between internal and external relation models.
In this sense either endogenous and exogenous models are able to determine relation based on causation or acausation. The difference between causation in endogenous models and exogenous models is based on the mechanism by which the causation operates. In particular in the case of endogenous models the causation is based on the internal relation between variables while in the case of exogenous models the causation model operates as a tool between internal and external variables.

The relation between causation and a-causation in respect to endogeneity and exogeneity causation and acausation Causation A-Causation Endogeneity
Main effect: The economic phenomena is determined in the context of analysis. Causation is determined for example in model developed by Romer able to explain economic conditions using endogeneity tools.
Main effect: Models are based on endogeneity but they can't affirm the existence of a certain definted causation effect. Modeling can just adfirm the existence of association among phenomena. Modeling technique: models are based on the relation between individual variables that are all endogenous. The focus is based on internal relationships and modeling.
Modeling technique: the elimination of the presumed endogenous cause does not generate the elimination of the estimated effect.

Exogeneity
Main Effect: the cause able to generate the economic phenomena is external in respect to the economic context. The absence of the external cause implies the nullification of the internal effect in the economic modeling.
Main effect: Models are based can't affirm the existence of a certain definted causation effect. Modeling can just adfirm the existence of association among phenomena.
Modeling technique: modeling are based on the relationship between internal and external variables.
Modeling technique: the elimination of the presumed exogenous cause does not eliminate the presence of estimated effect.

Database technology KNIME
We used Knime (Konstanz Information Miner) as data transformation and DSS technology, a data pipelining tool which enable to perform complex analysis tasks on potentially huge amounts of data. In this tool, the pipeline is formed from consecutively connected processing units called nodes. The raw input data can be read from various data sources, such as text files and databases. Typically, the data is remodeled into table-like representations. These tables are then passed along the pipeline to other nodes, which handle pre-processing such as normalizing numerical values, filtering rows based on specific criteria or joining tables from different branches of the workflow. Subsequent nodes then apply machine learning or data mining algorithms to build models based on the input data.
We performed a specific ETL (Extraction Transformation Load) for each data source, enforcing data quality and consistency standard, so that separate sources can be used together for analysis. The complete dataset has enabled the extraction of a set of Key Performance Indicators (KPI) for universities. These have been grouped in three domains 1. ORGANIZATIONAL EFFICIENCY In order to allow greater flexibility of the dashboard with respect to the needs of individual universities, the system has been designed so that the user can select a variable of interest from the front-end on which three different operations are performed in real time:  Construction of the historical series of values  Prediction of the evolution of the value for the following year, with an indication of the expected range of variability.
 Identification of the variables most closely related to the variable of interest.

Figure 4 Knime metanode for Outlier detection
In the context of prototype development, we limited the application of the prediction algorithms to the ARIMA (AutoRegressive Integrated Moving Average) model, which allows an effective interpolation of data with non-steady short-term trend and allows to identify the possible evolution of the monitored variable within a range subject to the influence of other variables. This feature is valuable in a business intelligence context where it is necessary to make choices in the short term (1 year) and on single expense items by identifying correlated variables.
The Outlier analysis allows the identification of financial statement anomalies, providing a useful tool to discover information otherwise shadowed. Outliers are defined as anomalous and out-of-average values, which can only be explained by particular conditions and can reveal potential resources not yet fully used.

Figure 5 Knime DSS front-end Global Universities Ranking and Equitable Sustainable Well-Being
We estimate the position of universities in the global ranking using a set of variables taken from the Istat-BES database. The objective of the regressions models performed with a Panel Data technique consists in the individualization of social and economic determinants that are associated with a higher performance of universities. The causation and causality effects are excluded from methodological and epistemological reasons, and sequently, the relations analyzed are twofold i.e.: on one side estimations express the impact of socio-economic determinants on the international university ranking. But on the other side these relations can be enforced also by universities in their attempt to change favorably the socio-economic environment to boost universities.
In effect universities are considered as social and economic institutions that can improve their international and local impact encouraging different set of stakeholders in being active in the sense of financial economics. In particular better universities are located in better communities defined in the sense of economic improvements, social relations, cultural environments, and the presence of quality of work and services. Due to this kind of socio-economic set of variables, universities can try to create new policies that can improve the positions of universities in the global ranking. The results of the analysis are in the appendix. In particular using data from ISTAT-BES and World Global University Ranking we estimate the sequent formula for italian universities: We found that the degree of Universities in global ranking has the sequent relations:  Employment: there is a negative relation between employment and the degree of universities in global ranking. The negative relation is due to the fact that were the level of employment is low, also the level of enrolment of students in universities is low. In effect the graduate and postgraduate education is realized to improve the probability of unemployed to be employed. But where unemployed is low, the incentive of workers to acquire a formal education is low, too. In effect employed workers have less motivations to be enroled in universities in respect to unemployed workers. Employed workers can be more interested in increasing their professional skills through courses realized in the corporate environment. Employed Workers are not interested in under graduate and postgraduate courses in universities.
 Predatory crimes: the relation between the rank of university in international rankings and the level of predatory crimes is negative. This means that universities in mean insist in territory characterized by low predatory crimes. The presence of violence, or the presence of criminals, reduce the quality of human and social capital, and reduce the ability of the university to acquire credibility using spillovers in respect to the social environment. Predatory crimes are the sign of low educated population and in this sense the possibility of the university to perform well in the context of international ranking is scarce. Universities are related to human capital, and they try to use these connections to increase their local, national and international background.
 Subjective well-being: the relation between the international ranking of universities and subjective well-being is negative. People that experiment a high level of subjective well-being is less motivated to study and be enrolled in the global competition of professional skills and competences. Subjective well-being can be considered as an approximation of happyness. Subjective well-being shows the presence of a level of life satisfaction that reduce the motivation of the people towards the efforts to learn a science, a profession, a skills. If universities are located in proximity with communities in which there is a high level of subjective well being, there are negative probabilities to obtain high level in global universities ranking due to the presence of a low motivated student population.
 Landscape: The relation between landscape and international university ranking is negative. Communities and territories that are located in proximity with beautiful landscape tend to invest less in universities in respect to places in which there is a low level of landscape quality. For example, in big cities where the quality of landscape is tendentially low there are good universities while on the other hand in universities located in periphery, where there is a good quality of landscape, the level of international ranking is low. Landscape is negatively associated to the high degree of international university ranking for the fact that good landscape is an approximation of peripheral areas and peripheral areas are in general associated with low degree in university rankings.
 Environment: the relation between environment and international university ranking in negative. A good quality of environment is negatively associated to a high level of international university ranking. In particular cities and communities that are characterized by high level of environment are generally in peripheral zones in which, tipically, the level of universities in global rankings is low. At the contrary universities that are located in cities, where the level of environment is generally low, or above the mean of the distribution, are characterized by high level in international universities rankings.
 Health: The relation between health and international university ranking is positive. There increase in the level of health of the population is associated to a higher level of university rankings. Universities that have an international high rank are also associated to more healthy population. The level of health of population growths in connection to healthcare services, and cities are able to offer more healthcare in respect to peripheral areas. In this sense there is a positive connection between the level of health of the population and the level of universities in the global ranking. Healthcare system especially in Italy are related to universities especially for the case of "Polyclinic" that are traditionally related to italian universities.
 Quality of work: The relation between international university ranking and quality of work is positive. Quality of work increases in relation to income and in urban cities. Low level of quality of work, is connected to marginal areas, in particular to areas that are characterized by low income and low servitization of the production. The quality of work declines when economies increase their production in the agricultural sector, or in construction or in manufacture. A good quality of work is associated to a development of economic system in the sense of service. Generally good universities are located in connection with cities in which the percentage of workers in the service sector is higher than in peripheral area.
 Income and Inequality: the relation between income and inequality and university internationl ranking is positive. The level of international ranking increases with the increasing level of income. The greater the income in the area in which the university is located the higher the level of the degree of ranking of universities in the international ranking. Generally, people with a higher income can pay higher fees to have access to universities and universities that have more found have also more probability to receive better evaluation in the international ranking.
 Social Relations: The relation between international university ranking and social relations is positive. The increase in the quality and quantity of social relations is associated to better performance of the universities in the global ranking. In particular universities needs to be installed in collaborative communities that can perform cooperative behaviors. Universities organize human and social capital and try to generate knowledge for communitarian purposes. In this sense deeper social relations in the communitarian environment can improve the performance of universities either in the global competition for excellence.
 Quality of services: The relation between university international university ranking and quality of services is positive. The presence of good quality of services is a sign of a developed economy. The increasing quality of services determine also a deeper level of sofistication of the economic process, that can be determined by a diffusion of scientific, technological and professional knowledge that generally is associated to the presence of high internationally ranked universities.
 Education: the relation between education and international university ranking is positive. A good university is determined in connection with a good educational system not only in the sense of graduate and postgraduate formation as in the sense of bachelor, masters and Ph.Ds but also in the sense of schools that can improve the level of knowledge in student population. At the end, also professional and technological educational system determine an increase in knowledge.
Based on the explained relation it is possible to determine connection between elements of the socio-economic condition of the communities and the presence of high ranked universities in the globalization. In particular the possibility for universities to receive a higher international rank depends on a complex set of social and economic factors that include also cultural and environmental features. In this sense it is clear that the presence of urban prosperous economies oriented to servitization and knowledge can be considered as an essential pre-requisite that can improve the performance of universities in global ranking. Anyway, the effect is twofold: not only good universities are associated to performing societies but also performing societies are associated to good universities.
Universities are the product of social and economic environment, and they can prosper only if there are multiple connections with various stakeholders. There are multiple stakeholders' approach can be used to understand the complex commitment that universities have in respect to communities and territories. In particular, to perform better universities require to be interconnected with the entrepreneurial system, the cultural environment, and the institutional order. In particular better universities participate of communities that are urban, oriented to the servitization, with good quality of work and services, and in which a not so high level of happiness widespread in the population. In this sense high performing universities in the international ranking are determined in connection to economic order orientated to globalization, servitization ad knowledge society. In effect servitization, globalization and knowledge society even in its definition of learning society, are able to generate an economic environment in which human and social capital can found naturally their anchoring in the university system.
The relation is twofold, and this means that italian universities that are interested in a better position in the international ranking have to promote communities that are oriented to quality of work and services, to higher income, better health, and more efficient education system either in the pre-universitarians degree of education. In this sense it is necessary to consider the impact of a university in the context of a certain economy as a sort of development economics politics that can be applied to produce an economic and social change in the societal environment.

The relation between global university ranking and almalaurea
In the sequent model we have estimated the impact of World University Ranking of italian universities based on a set of variables that are related to Almalaurea. Almalaurea is based on data based on italian laureates and offers a synthesis of a socio-economic conditions of italian students and former students. In particular we try to estimate if the level of international university ranking based on the characteristics of the student population. The results of the analysis are in the appendix. Our estimation is indicated in the follow relation: We perform a series of econometric model in the form of panel data with random and fixed effects.
 Enrolled in a special degree: there is a negative relation between being enrolled in a special degree and the level of university in the global ranking. The negative relation is due to the fact that universities in global ranks are oriented to realize especially research and development activities instead of pure educational activities.
 Enrolled in the same faculty to continue to study: There is a negative relation between the number of students enrolled in the same faculty to continue to study and the level of universities in the global ranking. The greater the number of students enrolled in the same faculty to continue to study the greater the level of university in the global and international rankings.
 Postgraduate formation: there is a negative relation between postgraduate formation and the degree of universities in the global university ranking. The greater the number of postgraduate students the lower the degree of universities in the international rankings.
 Internship and Apprenticenships: there is a negative relation between the number of internship and apprenticeships and the degree of universities in the global context. An increase in the number of internship and apprenticeships is connected with a decrease in the level of international rank of universities.
 Past worker unemployed: there is a negative relation between the number of past worker unemployed and the degree of universities in the international ranks. The greater the number of the past worker unemployed the lower the degree of universities in the international ranks.
 Graduates who continue previous work: there is a negative relation between the number of graduates who continue previous work and the degree of universities in international rank. The greater the number of graduates who continue previous work the lower the degree of universities in the international rank.
 Period from degree to first job: there is a negative relation between the period intervened between the degree and the first job and the position of universities in the global ranking. The longer the period intervened between the first degree and the first job and the lower the position of universities in the global ranks.
 Net Monthly Salary for Men: There is a negative relation between the monthly salary for men and the position of universities in the global ranking. The greater the monthly salary for men the higher the position of universities in the global rankings.
 Net Monthly salary for Women: There is a negative relation between monthly salary for women and the position of universities in the global rankings. The greater the monthly salary for woman the higher the position of universities in the global rankings.
 Job that require a degree 4 legal reasons: there is a negative relation between the number of jobs that require a degree for legal reasons and the position of universities in the global ranking. In particular the greater the number of jobs that require a degree for legal reasons the lower the positions of universities in the global rankings.
 Improvement in work due to grad: there is a negative relation between the number of students that have a improvement in work due to graduation and the position of universities in the global rankings. In particular the increasing of the number of people that has an improvement in work due to graduation is associated to a reduction in the position of universities in the global rankings.
 Satisfaction with the work done: there is a negative relation between the satisfaction of with the work done and the positions of universities in the global rankings. The increase in the satisfaction with work done is associated with a decline in the position of universities in the global rankings.
 Response rate: there is positive relation between the response rate of the student population and the position of universities in the global rankings. The increase in the response rate is associated with an increase in the position of universities in the global rankings.
 Compensation based on gender Man: there is a positive relation between the compensation based on gender especially for man and the position of universities in the global rankings. The increase in the compensation for male is associated with an increase in the position of universities in the global rankings.  Period to find first job: there is a positive relation between the period to find the first job and the position of universities in the global rankings. In particular the greater the period to find the first job for student population the higher the position of universities in global rankings.
 Public sector workers: there is a positive relation between the presence of public sector workers and the position of universities in the global rankings. In particular the increase in the number of public sector workers is associated to an increase in the position of universities in the global rankings.
 Jobs for which the degree is effective: there is a positive relation between the number of job position for which the degree is effective and the position of universities in the global rankings. In particular the increase in the number of jobs for which a degree is effective is associated to an increase in the position of universities global rankings.
 Inactive look 4 Works in the last 15 years: there is a positive relation between the presence of inactive people searching for work in the last 15 years and the position of universities in the global rankings. In particular the increase in the number of inactive employed that are searching for work in the last 15 years is associated to an increase in the position of universities global rankings.
We have estimated a series of variables to understand the effective relation between the position of universities in the global rankings and the characteristics of the student population and in general demographic population located in the same territory of the university. We find that more active population are generally associated with the presence of universities well-ranked at a global level. The best student population is interested not only in education but also in the culture trying to acquire not only knowledge not only for professional purpose or to acquire skills and competence. Universities require a demographic and cultural environment devoted to knowledge in general sense and not only for professional skills. But to improve motivation for excellence is also necessary a population that is not too satisfied with their jobs, since high degree of happiness and satisfaction of the population are negatively associated to an increase in the position of university global rankings.

Conclusion
In conclusion we can say that the presence of universities high positioned in the global rankings is determined by a set of variables defined either on a sociological point of view either demographic. Universities can improve their global rank creating better social and communitarian relationships. In particular universities that are located in communities that are more oriented to socially appreciate culture and knowledge have also better probabilities to increase their global ranking. In particular the presence of pro-active communities is essential not only to develop more performing universities operating at an international level but also to generate more efficient spillovers in respect to the same communities. Universities in fact can generate important positive externalities on a communitarian level especially in the sense of promoting technological and innovative effects in the productive context. More pro-active communities, that have higher sensibility in respect to culture and knowledge can favour the development of more innovative universities with greater impact also in the sense of organizational spillovers. Spillovers can impact the socio-economic condition of the population of a certain community determining further positive effect on the development of universities. In this sense it is important to analyze the role of universities in respect to their communities. In this sense we have affirmed the presence of a nexus between high performing universities and the presence of pro-active communities on a local level. But we have also showed skepticism about the possibility to consider the nexus in the sense of causality or causation: we can only say that a certain nexus exists, that these phenomena are associated but we can't adfirm the presence of a specific causality nexus. We can only affirm that certain phenomena are associated but we can't say if they are effectively in the order of causation of a causality.
Well performing universities are also more prone to be determined in connection with better student populations. In our analysis we have showed what are the characteristics of the student population that can sustain deeper performance of universities. In particular students that are more devoted to culture and knowledge, that consider universities as a tool to improve their personal and cultural abilities have more probabilities to perform better even in the global rankings. In this sense we can say that generally well-performing universities have good students but also that good students can generate well-performing universities. In our estimations we have found that the possibility for universities to better perform in a global environment are effectively related to presence of certain characteristics of the communities and in particular of the student population.

Limitations
The are three limitations in this article. The first limitation is the absence of the analysis of the connection between well performing universities and the local industrial and productive system. The second limitation is the presence of an excess of exogeneity in the relation between well ranked universities and well performing students. The exogeneity is difficult to eliminate due to the fact that high level of social capital in a certain territory is associated either to good universities either to well performing students. The third limitation is the fact that the dataset is only related to Italian universities and it does not consent to create international comparisons among different countries. The consequence of this limitation is the fact that the study can't be generalized without a preliminary analysis of the performance of nonitalian universities in comparison with italian universities. To remove these limitations it is necessary to continue the research increasing the dataset and applying techniques able to solve or better investigate the question of exogeneity.

Recommendation
Our analysis shows that better universities have better students. But either universities and students participate of the social, cultural and human capital of a certain territory. Policy makers and governmental institutions interested in the performance of universities should act increasing the value of social, cultural and human capital. In well-ordered society in which values such as cooperation, knowledge, human relations, are effectively performed, there is a high probability to develop either well-performing universities, either to have a good student population. Policy makers and institutions can operate either endogenously either exogenously, designing better incentives and promoting a society more oriented to culture and knowledge. It is important also to implement policies able to create connections between the industrial system and the university system especially in the field of innovation and new technologies. If policy makers are able to increase the level of general trust in institutions and are capable to design incentives to increase the degree of knowledge and culture either in non-profit organization either in the industrial and manufactural sector, then the population can have extrinsic and intrinsic motivations to engage universities not only as a way to obtain professional knowledge but also interiorizing the need for a virtuous life based on culture. Policy makers have to promote either a better efficient university system either a better student population more oriented to culture and knowledge. The combination of more efficient universities and more performing student population can have a relevant impact on the ability of the society as a whole to generate values either in the industrial system either in the cultural environment.