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The well-being generated by each place is an unobservable characteristic affecting local competitiveness and territorial growth. In evaluating local well-being, the use of residents’ perceptions may generate biased evaluations. Alternatively, a revealed-preference analysis of tourists’ happiness might be exploited to assess the quality of life at the destination. Then, we develop a hedonic utility function to analyze a huge and original dataset of foreign tourists’ satisfaction, visiting Italy over 2005-2014, on a large number of place-based amenities. Results show a great diversity in the mix of features that affect tourist well-being at each destination, indicating strong heterogeneity in place-based amenities, correlated in space. The presence of spatially correlated common factors of competitiveness asks for coordinated action plans on the part of local and regional authorities.

The well-being generated by each place is an unobservable characteristic affecting local competitiveness and territorial growth. In evaluating local well-being, the use of residents’ perceptions may generate biased evaluations. Alternatively, a revealed-preference analysis of tourists’ happiness might be exploited to assess the quality of life at the destination. Then, we develop a hedonic utility function to analyze a huge and original dataset of foreign tourists’ satisfaction, visiting Italy over 2005-2014, on a large number of place-based amenities. Results show a great diversity in the mix of features that affect tourist well-being at each destination, indicating strong heterogeneity in place-based amenities, correlated in space. The presence of spatially correlated common factors of competitiveness asks for coordinated action plans on the part of local and regional authorities.

This paper shows that a suitable decomposition of TFP can be applied to a large sample of subsidized firms for a relevant period of time, allowing an evaluation of the impact of subsidies on either the roles of technical progress and technical efficiency change or scale and allocative efficiency change as determinants of granted firms’ long-term growth. We measure and decompose TFP using a Stochastic Frontier Analysis (SFA). The impact of capital subsidies on the different components of TFP is captured by a quasi–experimental method (Multiple RDD), exploiting the conditions for a local random experiment created by Law 488/92 (L488), which has been an important policy instrument for reducing territorial disparities in Italy. The main findings from the case study are twofold. First, capital subsidies positively affect TFP growth in the medium-long term and not in the short term. The main reason is that allocative efficiency has a positive effect only after 2-3 years. Second, the positive impact comes especially through technical progress and not through scale impact change, as may have been expected.

This paper shows that a suitable decomposition of TFP can be applied to a large sample of subsidized firms for a relevant period of time, allowing an evaluation of the impact of subsidies on either the roles of technical progress and technical efficiency change or scale and allocative efficiency change as determinants of granted firms’ long-term growth. We measure and decompose TFP using a Stochastic Frontier Analysis (SFA). The impact of capital subsidies on the different components of TFP is captured by a quasi–experimental method (Multiple RDD), exploiting the conditions for a local random experiment created by Law 488/92 (L488), which has been an important policy instrument for reducing territorial disparities in Italy. The main findings from the case study are twofold. First, capital subsidies positively affect TFP growth in the medium-long term and not in the short term. The main reason is that allocative efficiency has a positive effect only after 2-3 years. Second, the positive impact comes especially through technical progress and not through scale impact change, as may have been expected.

A fil rouge runs through the papers presented in this Issue of the Review: the idea that the tourist development is less and less related to the distinct touristic attractions of a region and more and more to the contest where the tourist attractions lie. Clearly, not every region is suitable for tourist and recreation mission. However, policy makers have several opportunities in order to find the appropriate strategic decisions in tourism planning and to obtain sustainable and smart growth.

A fil rouge runs through the papers presented in this Issue of the Review: the idea that the tourist development is less and less related to the distinct touristic attractions of a region and more and more to the contest where the tourist attractions lie. Clearly, not every region is suitable for tourist and recreation mission. However, policy makers have several opportunities in order to find the appropriate strategic decisions in tourism planning and to obtain sustainable and smart growth.

This PhD thesis aims at providing an evaluation of EU Cohesion policy impact on regional growth. It employs methodologies and data sources never before applied for this purpose. Main contributions to the literature concerning EU regional policy effectiveness have been extensively analysed. Moreover, having carried out an overview of the current literature on Cohesion Policy, we deduce that this work introduces innovative features in the field. The work enriches the current literature with regards to two aspects. The first aspect concerns the use of the instrument of Regression Discontinuity Design in order to examine the presence of a different outcome in terms of growth between Objectives 1 regions and non-Objective 1 regions at the cut-off point (75 percent of EU-15 GDP per capita in PPS) during the two programming periods, 1994-1999 and 2000-2006. The results confirm a significant difference higher than 0.5 percent per year between the two groups. The other empirical evaluation regards the study of a cross-section regression model based on the convergence theory that analyses the dependence relation between regional per capita growth and EU Cohesion policy expenditure in several fields of interventions. We have built a very fine dataset of spending variables (certified expenditure), using sources of data directly provided from the Regional Policy Directorate of the European Commission.

This PhD thesis aims at providing an evaluation of EU Cohesion policy impact on regional growth. It employs methodologies and data sources never before applied for this purpose. Main contributions to the literature concerning EU regional policy effectiveness have been extensively analysed. Moreover, having carried out an overview of the current literature on Cohesion Policy, we deduce that this work introduces innovative features in the field. The work enriches the current literature with regards to two aspects. The first aspect concerns the use of the instrument of Regression Discontinuity Design in order to examine the presence of a different outcome in terms of growth between Objectives 1 regions and non-Objective 1 regions at the cut-off point (75 percent of EU-15 GDP per capita in PPS) during the two programming periods, 1994-1999 and 2000-2006. The results confirm a significant difference higher than 0.5 percent per year between the two groups. The other empirical evaluation regards the study of a cross-section regression model based on the convergence theory that analyses the dependence relation between regional per capita growth and EU Cohesion policy expenditure in several fields of interventions. We have built a very fine dataset of spending variables (certified expenditure), using sources of data directly provided from the Regional Policy Directorate of the European Commission.

Produttività ed efficienza sono termini comunemente utilizzati per caratterizzare l’abilità di un’impresa nell’utilizzazione delle risorse, sia in ambito privato che pubblico. Entrambi i concetti sono legati da una teoria della produzione che diventa essenziale per la determinazione dei criteri base con i quali confrontare i risultati dell’attività produttiva e i fattori impiegati per ottenerli. D’altronde, le imprese scelgono di produrre e di investire sulla base delle proprie prospettive di mercato e di costi dei fattori. Quest’ultimi possono essere influenzati dalle politiche dello Stato che fornisce incentivi e sussidi allo scopo di modificare le decisioni riguardanti l’allocazione e la crescita delle imprese. In questo caso le stesse imprese possono preferire di non collocarsi nell’equilibrio produttivo ottimo, massimizzando produttività ed efficienza, per poter invece utilizzare tali incentivi. In questo caso gli stessi incentivi potrebbero distorcere quindi l’allocazione delle risorse delle imprese che sono agevolate. L’obiettivo di questo lavoro è quello di valutare attraverso metodologie parametriche e non parametriche se incentivi erogati dalla L. 488/92, la principale politica regionale in Italia nelle regioni meridionali del paese nel periodo 1995-2004, hanno avuto o meno effetti sulla produttività totale dei fattori delle imprese agevolate. Si è condotta una ricognizione rispetto ai principali lavori proposti in letteratura riguardanti la TFP e l’aiuto alle imprese attraverso incentivi al capitale e (in parte) dell’efficienza. La stima della produttività totale dei fattori richiede di specificare una funzione di produzione ponendo l’attenzione su modelli di tipo parametrico che prevedono, quindi, la specificazione di una determinata forma funzionale relativa a variabili concernenti i fattori di produzione. Da questa si è ricavata la Total Factor Productivity utilizzata nell’analisi empirica che è la misura su cui viene valutata l’efficienza produttiva d

Produttività ed efficienza sono termini comunemente utilizzati per caratterizzare l’abilità di un’impresa nell’utilizzazione delle risorse, sia in ambito privato che pubblico. Entrambi i concetti sono legati da una teoria della produzione che diventa essenziale per la determinazione dei criteri base con i quali confrontare i risultati dell’attività produttiva e i fattori impiegati per ottenerli. D’altronde, le imprese scelgono di produrre e di investire sulla base delle proprie prospettive di mercato e di costi dei fattori. Quest’ultimi possono essere influenzati dalle politiche dello Stato che fornisce incentivi e sussidi allo scopo di modificare le decisioni riguardanti l’allocazione e la crescita delle imprese. In questo caso le stesse imprese possono preferire di non collocarsi nell’equilibrio produttivo ottimo, massimizzando produttività ed efficienza, per poter invece utilizzare tali incentivi. In questo caso gli stessi incentivi potrebbero distorcere quindi l’allocazione delle risorse delle imprese che sono agevolate. L’obiettivo di questo lavoro è quello di valutare attraverso metodologie parametriche e non parametriche se incentivi erogati dalla L. 488/92, la principale politica regionale in Italia nelle regioni meridionali del paese nel periodo 1995-2004, hanno avuto o meno effetti sulla produttività totale dei fattori delle imprese agevolate. Si è condotta una ricognizione rispetto ai principali lavori proposti in letteratura riguardanti la TFP e l’aiuto alle imprese attraverso incentivi al capitale e (in parte) dell’efficienza. La stima della produttività totale dei fattori richiede di specificare una funzione di produzione ponendo l’attenzione su modelli di tipo parametrico che prevedono, quindi, la specificazione di una determinata forma funzionale relativa a variabili concernenti i fattori di produzione. Da questa si è ricavata la Total Factor Productivity utilizzata nell’analisi empirica che è la misura su cui viene valutata l’efficienza produttiva d

Extensive and persistent geographic variability of the unemployment rate within the same region has been attributed to various causes. Some theories identify the “thickness” of markets as the source of positive externalities affecting labour market by improving the ability to match the skills requested by firms with those offered by workers. A recent paper by Gan and Zhang (2006) empirically confirms this hypothesis for the US labour markets. Agglomeration can be defined as aggregation of people, basically measured by city size, or as aggregation of firms, measured by cluster size (employment or number of plants). However, the population location and the industrial location are by far more similar in United States than in Europe and in Italy. Our paper aims to evaluate the effects of agglomeration on the local unemployment rate. The new methodological contribution of the study is the identification of both urban and industrial cluster agglomeration effects, using a wide set of control variables. Adjusting the system for the effects of sectorial and size shocks, as well as those relating to geographic structure and policy interventions, the results of our analysis differ from that for the United States. The study stresses the presence of negative and significant urbanisation externalities. We obtain, instead, positive effects concerning the geographic agglomeration of firms, and their thickness, in a specific area. Furthermore, positive and significant effects can be found in local systems with features of a district. Finally, the model distinguishes the negative effects of urban agglomerations (in terms of population density) from positive firm’s agglomerations (in terms of density of local units).

Nonparametric analysis of shape and dynamics of probability distributions has recently been used to identify clustering and polarization phenomena in regional economic development (Quah, 1997 a, b). The technique used to investigate which variables are relevant in determining such polarization phenomena is known as conditioning. So far this kind of approach has been applied only in a univariate context. In this paper, we propose a more general framework, referring to the literature on nonparametric local regression techniques. Following this alternative approach we are able to study the joint effect of two or more variables on the shape of the distribution of growth. An empirical illustration is given for the distribution of employment rate in 784 Italian Local Labour Markets.

The paper evaluates the statistical properties of two different matching estimators in the case of continuous treatment, using a Montecarlo experiment. The traditional generalized propensity score matching estimator is compared whit a new two steps matching estimator for the continuous treatment case, recently developed (Adorno, Bernini, Pellegrini, 2007). It compares treatment and control units similar in terms of their observable characteristics in both selection processes (the participation decision and the treatment level assignment), where the generalized propensity score matching estimator collapses the two processes into one single step matching. The results show that the two steps estimator has better finite sample properties if some institutional rules define the level of treatment with respect to the characteristics of treated units.

The paper evaluates the statistical properties of two different matching estimators in the case of continuous treatment, using a Montecarlo experiment. The traditional generalized propensity score matching estimator is compared whit a new two steps matching estimator for the continuous treatment case, recently developed (Adorno, Bernini, Pellegrini, 2007). It compares treatment and control units similar in terms of their observable characteristics in both selection processes (the participation decision and the treatment level assignment), where the generalized propensity score matching estimator collapses the two processes into one single step matching. The results show that the two steps estimator has better finite sample properties if some institutional rules define the level of treatment with respect to the characteristics of treated units.