Vincenzo Larosa (p), Angela Stefania Bergantino

Social capital is strictly linked to the quality of institutions and determines their performance. Nevertheless, social capital as a multidimensional phenomenon is difficult to quantify. According to OECD, social capital is defined as “networks together with shared norms, values and understandings that facilitate co-operation within or among groups''. How to measure social capital is not widely accepted and it has become a debate in itself. The quantitative measuring has proven somewhat complicated that has resulted in different metrics for different dimensions. In the literature, its dimensions have been assessed through direct indicators (as voluntary associations, and social interaction and networks) and indirect indicators (newspaper diffusion, crime rates, political participation, blood donation (Putnam, 1993; Guiso, Sapienza, Zingales, 2004). Also, these measures may occur at different territorial levels. For instance, in Italy, the social capital and the quality of the institutions are phenomena rooted in the communities, which differ within the country by pointing out an important territorial aspect of the phenomenon (Putnam, 1993, 2000).
This work aims to explain the drivers that favour institutional quality, at the provincial level, in the period between 2007 and 2012. Through investigating the level of institutional quality by using the Institutional Quality Index (Nifo and Vecchione, 2014), we test some additional variables beside of the classical ones that we think better determine the social capital. We collect data at Italian provincial level of socio-demographic, institutional and economic context variables, as well as of crime against PA, gender equity, social inclusion, waste management, research and development indicators. Using a panel data analysis, we study the impact of different variables that delineate social capital on institutional quality level. Moreover, the reverse causality between institutional quality and social capital is explored. Our work contributes to the literature on two ways: first, from the different institutional level considered (province level/EU-NUTS3) and second, for a more comprehensive concept of social capital.

Eleonora Cutrini (p)

The attention to regional income inequality in Europe rebounded after the global financial crisis and focused on the different capacity of regions to overcome the Great recession. The characteristics ensuring regional resilience were deeply investigated (Martin, 2012; Martin et al., 2016) and one of the issues at the heart of the current debate is the question whether heterogeneous structural change is a driving force of divergence.
In a recent work (Cutrini, 2019) we provide evidence that European regions are scattered in five separate groups converging to their own steady state paths. Results suggest that the divergence among clusters is explained quite well by the structural characteristics of regions and their initial conditions. Particularly, a solid manufacturing base and specialization in high-productivity services both enhance growth, while low-skilled services are less relevant or even deteriorate growth prospects.
Sharing the view that institutions matter for regional development (Rodríguez-Pose, 2013; Ezcurra and Rios, 2019), this paper extends the previous analysis and examines the relationship between institutional quality and regional disparities in the European Union. To this purpose, we conduct an empirical analysis to evaluate whether the quality of government can indeed explain to which club the region converges during the period 2003-2016.
We collected a panel data on per capita income covering 274 EU regions during the period 2003-2016. For the covariates related to structural variables and human capital we refer to regional economic accounts, regional branch accounts, regional education statistics (Source: Eurostat). To measure institutional quality we use data on European Quality of Government Index (EQI), which has recently been constructed on the basis of the perceptions and experiences of European citizens on the quality, impartiality and level of corruption in education, public health care and law enforcement (Charron et al., 2014, 2015). We address endogeneity and econometric drawbacks by means of the dynamic panel generalized method of moments (GMM) estimator devised by Blundell and Bond (1998).
Main references:
Charron, N., Dijkstra, L. and Lapuente, V. (2014): Regional governance matters: quality of government within European Union member states, Regional Studies 48 (1), 68-90
Cutrini, E. (2019), Economic integration, structural change, and uneven development in the European Union, Structural Change and Economic Dynamics, Forthcoming
Ezcurra R., Rios V. (2019), Quality of government and regional resilience in the European Union. Evidence from the Great Recession, Papers in Regional Science
Rodríguez-Pose, A. (2013), Do Institutions Matter for Regional Development?, Regional Studies, 47(7), 1034–1047

Shaul Hartal (p)

Many cities want to be the ‘next Silicon Valley’. Most of them won’t get there. This study offers a new approach to deal with thriving or failing of clusters, based on an institutional analysis. I offer to investigate the role of spillover effect and its transaction costs, among actors co-locating in second-tier metropolitan's clusters.
The idea of voluntary sharing of knowledge is the main reason to co-locate knowledgeable people from different sectors in one place. The spillover effect that occurs among them boosts innovation. This assumption presupposes free trade market of ideas - but it avoids dealing with institutional constraints that may increase the transaction costs for individuals. These constraints can occur due to some reasons: a) knowledge workers from different sectors don’t usually meet on a professional basis; b) they don’t share the same formal roles, norms, and sanctions of people from the same milieu; c) they often use different technical terms, and d) they have different career incentives. When these costs are too high, they avoid sharing knowledge. In an aggregate way, it may lead to failure of the whole cluster.
The research question is: what are the transaction costs involved over spillover effect between cross-sector actors located in the same cluster? This study is based on Coase theorem as the main theoretical framework. I seek to identify these transaction costs, by developing a model that includes: a) group identity, b) network costs, c) social capital among people in the same milieu, d) control variables for individuals (e.g. gender, age) and for the cluster in which they are located (e.g. size, structure). I will deliver questionnaires to actors from different sectors – academy, industry and governmental institutes (e.g. hospitals). Data will be collected from a sample of 750 knowledge workers, divided equally between these three sectors. The data will be analyzed with structural equation models (SEM).
This study has a geographic perspective as well. The main interest is in clusters located in second-tier metropolitans. Innovation, creativity, and entrepreneurship provide an opportunity for regions to compete nationally and globally.
The results will enable to design a public policy that will help to create sustainable and competitive knowledge communities in second-tier metropolitans. I will present at the conference the results of a preliminary qualitative research.

Suzana Quinet Bastos (p), Fabio Gamma, Tiana Assis

In the present study, we ventured to investigate the role political and economic institutions have in promoting the human capital factor in the Lucas model (1988). The discussion proposed by Acemoglu et al (2014) and Acemoglu et al (2012) on institutional quality as responsible for the variations in the levels of human capital presented by the countries, elucidates how the incentives and safeguards promoted by political and economic institutions foster the growth process via human capital.
The results of estimations via pooled ordinary least squares estimation (POLS) and instrumental variables (IV) compare the variables that compose the Lucas growth model (1) to the same model of Lucas in an extended form (2), obtained by the insertion of institutions as boosters for the human capital stock. As predicted by the authors, the level of a country's political and economic institutions plays a significant role in economic growth via human capital, and it can be seen that the original Lucas model overestimates the contribution of human capital to growth, since it does not model institutions as one of its determinants.
Hence, as predicted by Acemoglu et al (2014), one can understand physical capital and human capital as proximate causes of economic growth. The comparative analysis between the Lucas model (1988) and the extended model proposed in the present study aims to indicate the overestimation in the effect of human capital on the output produced by the first one, since it does not consider institutions and human capital as correlated factors, notwithstanding, as discussed in Acemoglu et al. (2014), the human capital factor is determined institutionally and serves as an influence channel on institutions.
As presented in our study, the discussion concerning the impact of institutional composition on the level of economic prosperity continues to be reinforced through the empirical findings. Relying on the analysis of Acemoglu et al (2012), we can point a robust and independent judiciary power as a central effort in order to assure institutions to be channels operating under what the de jure power states, self-oriented for general benefit - and not under the influence of individuals or small groups. The relation between institutions and resources distribution in society, therefore, reinforces the constant need for policing our institutions and also suggests a better level of income distribution as an important mechanism for promoting more inclusive institutions in countries.