Building Synthetic Indicators For Aspects Of Territorial Capital Towards Their Impact On Regional Performance

Empirical analyses highlight local structural features (territorial capital) as constraints on regional growth and interregional convergence processes, but scant attention is devoted to traditional localised resources and specifically the natural and cultural heritage. However, only the application of know-how embodied in human capital to resources provides value. Specifically, heritage becomes economically relevant through human capital acting via tourist, recreational and cultural activities. Although, because of its service exporting nature, tourism contributes to economic growth and job creation similarly to manufacturing, the literature concerned manufacturing and rarely studied tourism or extended results to it. Besides, in Europe tourism is the market activity most favouring policentricity, territorial cohesion and equity. On the other hand, heritage valorisation responding to tourist service demand has adverse effects on development (congestion) and environmental quality / resource consumption (heritage dissipation); these partly offset strictly economic benefits and over time weaken the destination's pull, hence its value and its population's welfare. Our goal is to analyse the role of territorial capital, and specifically of intangibles such as natural and cultural capital, in regional growth processes and in local response processes to exogenous crises, by building a national database of territorial capital in Italian provinces, containing synthetic endowment indicators for natural and cultural heritage, human capital, and structure and distribution of tourism and leisure industries. Our methodology includes the application of multivariate analyses, with state-of-the-art techniques. We use available European and national databases, augmented by ad hoc integrations if and when needed. The study area is Italy; the optimal tier is NUTS3, i.e. provinces, in Italy. The time reference is 1990-2010, to ensure a structural long-term approach. The paper is organised in the following way: - an initial section outlines the original data on 103 provinces, providing 33 proxy indicators of which major univariate statistics and correlations are explored; - a first main section reduces indicators into 5 synthetic indicators, by means of factor analysis; - a second main section reduces provinces into 11 ideal types, by means of cluster analysis; - a final section compares and interprets results, also with reference to 2007-2009 economic dynamics.