La valutazione degli effetti delle politiche di coesione dell'Unione europea sulla crescita regionale

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.

Essays in policy evaluation

This dissertation consists of three empirical studies that aim at providing new evidence in the field of public policy evaluation. In particular, the first two chapters focus on the effects of the European cohesion policy, while the third chapter assesses the effectiveness of Italian labour market incentives in reducing long-term unemployment. The first study analyses the effect of EU funds on life satisfaction across European regions , under the assumption that projects financed by structural funds in the fields of employment, education, health and environment may affect the overall quality of life in recipient regions. Using regional data from the European Social Survey in 2002-2006, it resorts to a regression discontinuity design, where the discontinuity is provided by the institutional framework of the policy. The second study aims at estimating the impact of large transfers from a centralized authority to a local administration on the incidence of white collar crimes. It merges a unique dataset on crimes committed in Italian municipalities between 2007 and 2011 with information on the disbursement of EU structural funds in 2007-2013 programming period, employing an instrumental variable estimation strategy that exploits the variation in the electoral cycle at local level. The third study analyses the impact of an Italian labour market policy that allowed firms to cut their labour costs on open-ended job contracts when hiring long-term unemployed workers. It takes advantage of a unique dataset that draws information from the unemployment lists in Veneto region and it resorts to a regression discontinuity approach to estimate the effect of the policy on the job finding rate of long-term unemployed workers.

Detection and Modeling of Boundary Layer Height

This thesis tackles the problem of the automated detection of the atmospheric boundary layer (BL) height, h, from aerosol lidar/ceilometer observations. A new method, the Bayesian Selective Method (BSM), is presented. It implements a Bayesian statistical inference procedure which combines in an statistically optimal way different sources of information. Firstly atmospheric stratification boundaries are located from discontinuities in the ceilometer back-scattered signal. The BSM then identifies the discontinuity edge that has the highest probability to effectively mark the BL height. Information from the contemporaneus physical boundary layer model simulations and a climatological dataset of BL height evolution are combined in the assimilation framework to assist this choice. The BSM algorithm has been tested for four months of continuous ceilometer measurements collected during the BASE:ALFA project and is shown to realistically diagnose the BL depth evolution in many different weather conditions. Then the BASE:ALFA dataset is used to investigate the boundary layer structure in stable conditions. Functions from the Obukhov similarity theory are used as regression curves to fit observed velocity and temperature profiles in the lower half of the stable boundary layer. Surface fluxes of heat and momentum are best-fitting parameters in this exercise and are compared with what measured by a sonic anemometer. The comparison shows remarkable discrepancies, more evident in cases for which the bulk Richardson number turns out to be quite large. This analysis supports earlier results, that surface turbulent fluxes are not the appropriate scaling parameters for profiles of mean quantities in very stable conditions. One of the practical consequences is that boundary layer height diagnostic formulations which mainly rely on surface fluxes are in disagreement to what obtained by inspecting co-located radiosounding profiles.