Politiche Antitrust e crescita economica

Negli ultimi anni le istituzioni e la regolamentazione hanno svolto un ruolo sempre più importante nell’analisi della crescita economica. Tuttavia, non è facile interpretare le istituzioni e gli effetti dei regolamenti sulla crescita attraverso indicatori che tendono a “misurare” le istituzioni. Lo scopo di questa ricerca è analizzare la relazione di lungo periodo tra la crescita economica e la regolamentazione e il ruolo della regolamentazione antitrust sulla crescita economica. La stima econometrica dei modelli di crescita con la concorrenza e gli indicatori di potere di mercato si base su un dataset appositamente costruito che copre 211 Paesi, su un arco temporale massimo di 50 anni (da 1960 a 2009). In particolare, cerchiamo di identificare un quadro analitico volto a integrare l’analisi istituzionale ed economica al fine di valutare il ruolo della regolamentazione e, più in generale, il ruolo delle istituzioni nella crescita economica. Dopo una revisione della letteratura teorica ed empirica sulla crescita e le istituzioni, vi presentiamo l’analisi dell'impatto normativo (RIA) in materia di concorrenza, e analizziamo le principali misure di regolamentazione, la governance e le misure antitrust. Per rispondere alla nostra domanda di ricerca si stimano modelli di crescita prendendo in considerazione tre diverse misure di regolamentazione: la Regulation Impact (RI), la Governance (GOV), e la libertà economica (LIB). Nel modello a effetti fissi, RI, gli effetti della legislazione antitrust sulla crescita economica sono significativi e positivi, e gli effetti di durata antitrust sono significativi, ma negativi. Nel pannel dinamico, GOV, gli effetti dell’indicatore di governance sulla crescita sono notevoli, ma negativo. Nel pannel dinamico, LIB, gli effetti della LIB sono significativi e negativi.

Analysis of the Slow Food movement impact on the farmers and rural areas’ sustainable development

The evaluation of the farmers’ communities’ approach to the Slow Food vision, their perception of the Slow Food role in supporting their activity and their appreciation and expectations from participating in the event of Mother Earth were studied. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was adopted in an agro-food sector context. A survey was conducted, 120 questionnaires from farmers attending the Mother Earth in Turin in 2010 were collected. The descriptive statistical analysis showed that both Slow Food membership and participation to Mother Earth Meeting were much appreciated for the support provided to their business and the contribution to a more sustainable and fair development. A positive social, environmental and psychological impact on farmers also resulted. Results showed also an interesting perspective on the possible universality of the Slow Food and Mother Earth values. Farmers declared that Slow Food is supporting them by preserving the biodiversity and orienting them to the use of local resources and reducing the chemical inputs. Many farmers mentioned the language/culture and administration/bureaucratic issues as an obstacle to be a member in the movement and to participate to the event. Participation to Mother Earth gives an opportunity to exchange information with other farmers’ communities and to participate to seminars and debates, helpful for their business development. The absolute majority of positive answers associated to the farmers’ willingness to relate to Slow Food and participate to the next Mother Earth editions negatively influenced the UTAUT model results. A factor analysis showed that the variables associated to the UTAUT model constructs Performance Expectancy and Effort Expectancy were consistent, able to explain the construct variability, and their measurement reliable. Their inclusion in a simplest Technology Acceptance Model could be considered in future researches.

Statistical analysis of the error associated with the simplification of the stratigraphy in geotechnical models

The uncertainties in the determination of the stratigraphic profile of natural soils is one of the main problems in geotechnics, in particular for landslide characterization and modeling. The study deals with a new approach in geotechnical modeling which relays on a stochastic generation of different soil layers distributions, following a boolean logic – the method has been thus called BoSG (Boolean Stochastic Generation). In this way, it is possible to randomize the presence of a specific material interdigitated in a uniform matrix. In the building of a geotechnical model it is generally common to discard some stratigraphic data in order to simplify the model itself, assuming that the significance of the results of the modeling procedure would not be affected. With the proposed technique it is possible to quantify the error associated with this simplification. Moreover, it could be used to determine the most significant zones where eventual further investigations and surveys would be more effective to build the geotechnical model of the slope. The commercial software FLAC was used for the 2D and 3D geotechnical model. The distribution of the materials was randomized through a specifically coded MatLab program that automatically generates text files, each of them representing a specific soil configuration. Besides, a routine was designed to automate the computation of FLAC with the different data files in order to maximize the sample number. The methodology is applied with reference to a simplified slope in 2D, a simplified slope in 3D and an actual landslide, namely the Mortisa mudslide (Cortina d’Ampezzo, BL, Italy). However, it could be extended to numerous different cases, especially for hydrogeological analysis and landslide stability assessment, in different geological and geomorphological contexts.