Effetti degli accordi Euro-Mediterrani sul comparto dell'ortofrutta fresca

In 1995, the European Union (EU) Member States and 12 Mediterranean countries launched in Barcelona a liberalization process that aims at establishing a free trade area (to be realized by 2010) and at promoting a sustainable and balanced economic development by the adoption of a new generation of Agreements: the Euro-Mediterranean Agreements (EMA). For the Mediterranean partner countries, the main concern is a better access for their fruit and vegetable exports to the European market. These products represent the main exports of these countries, and the EU is their first trading partner. On the other side, for the EU the main issue is not only the promotion of its products, but also the protection of its fruit and vegetables producers. Moreover, the trade with third countries is the key element of the Common Market Organization of the sector. Fruit and vegetables represent a very sensitive sector since their high seasonality, high perishability, and especially since the production of the Mediterranean countries is often similar to the European Mediterranean’s countries one. In fact, the agreements define preferences at the entrance of the EU market providing limited concessions for each partner, for specific products, limited quantities and calendars. This research tries to analyze the bilateral trade volume for fresh fruit and vegetables in the European and Italian markets in order to assess the effects of Mediterranean liberalization on this sector. Free trade of agricultural products represents a very actual topic in international trade and the Mediterranean countries, recognised as big producers of fruit and vegetables, as big exporters of their crops and actually significantly present on the European market, could be high competitors with the inward production because the outlet could be the same. The goal of this study is to provide some considerations about the competitiveness of mediterranean fruit and vegetables productions after Barcelona Process, in a first step for the European market and then also for the Italian one. The aim is to discuss the influence of the euro-mediterranean agreements on the fruit and vegetables trade between 10 foreign Mediterranean countries (Algeria, Egypt, Israel, Jordan, Libya, Lebanon, Morocco, Tunisia, Syria, and Turkey) and 15 EU countries in the period 1995-2007, by means of a gravity model, which is a widespread methodology in international trade analysis. The basic idea of gravity models is that bilateral trade from one country to another (as the dependent variable) can be explained by a set of factors: - factors that capture the potential of a country to export goods and services; - factors that capture the propensity of a country to imports goods and services; - any other forces that either attract or inhibit bilateral trade. This analysis compares only imports’ flows by Europe and by Italy (in volumes) from Mediterranean countries, since the exports’ flows toward those foreign countries are not significant, especially for Italy. The market of fruit and vegetables appears as a high heterogeneous group so it is very difficult to show a synthesis of the analysis performed and the related results. In fact, this sector includes the so called “poor products” (such as potatoes and legumes), and the “rich product”, such as nuts or exotic fruit, and there are a lot of different goods that arouse a dissimilar consumer demand which directly influence the import requirements. Fruit and vegetables sector includes products with extremely different biological cycles, leading to a very unlike seasonality. Moreover, the Mediterranean area appears as a highly heterogeneous bloc, including countries which differ from the others for economic size, production potential, capability to export and for the relationships with the EU. The econometric estimation includes 68 analyses, 34 of which considering the European import and 34 the Italian import and the products are examined in their aggregated form and in their disaggregated level. The analysis obtains a very high R2 coefficient, which means that the methodology is able to assess the import effects on fruit and vegetables associated to the Association Agreements, preferential tariffs, regional integration, and others information involved in the equation. The empirical analysis suggests that fruits and vegetables trade flows are well explained by some parameters: size of the involved countries (especially GDP and population of the Mediterranean countries); distances; prices of imported products; local production for the aggregated products; preferential expressed tariffs like duty free; sub-regional agreements that enforce the export capability. The euro-mediterranean agreements are significant in some of the performed analysis, confirming the slow and gradual evolution of euro- Mediterranean liberalization. The euro-mediterranean liberalization provides opportunities from one side, and imposes a new important challenge from the other side. For the EU the chance is that fruit and vegetables imported from the mediterranean area represent a support for local supply and a possibility to increase the range of products existing on the market. The challenge regards the competition of foreign products with the local ones since the types of productions are similar and markets coincide, especially in the Italian issue. We need to apply a strategy based not on a trade antagonism, but on the realization of a common plane market with the Mediterranean countries. This goal could be achieved enhancing the industrial cooperation in addition to commercial relationships, and increasing investments’ flows in the Mediterranean countries aiming at transforming those countries from potential competitors to trade partners and creating new commercial policies to export towards extra European countries.

Modeling the spatial dynamics of economic models

The advances that have been characterizing spatial econometrics in recent years are mostly theoretical and have not found an extensive empirical application yet. In this work we aim at supplying a review of the main tools of spatial econometrics and to show an empirical application for one of the most recently introduced estimators. Despite the numerous alternatives that the econometric theory provides for the treatment of spatial (and spatiotemporal) data, empirical analyses are still limited by the lack of availability of the correspondent routines in statistical and econometric software. Spatiotemporal modeling represents one of the most recent developments in spatial econometric theory and the finite sample properties of the estimators that have been proposed are currently being tested in the literature. We provide a comparison between some estimators (a quasi-maximum likelihood, QML, estimator and some GMM-type estimators) for a fixed effects dynamic panel data model under certain conditions, by means of a Monte Carlo simulation analysis. We focus on different settings, which are characterized either by fully stable or quasi-unit root series. We also investigate the extent of the bias that is caused by a non-spatial estimation of a model when the data are characterized by different degrees of spatial dependence. Finally, we provide an empirical application of a QML estimator for a time-space dynamic model which includes a temporal, a spatial and a spatiotemporal lag of the dependent variable. This is done by choosing a relevant and prolific field of analysis, in which spatial econometrics has only found limited space so far, in order to explore the value-added of considering the spatial dimension of the data. In particular, we study the determinants of cropland value in Midwestern U.S.A. in the years 1971-2009, by taking the present value model (PVM) as the theoretical framework of analysis.

Modelli non lineari statici e dinamici su dati microeconomici: analisi delle condizioni finanziarie delle famiglie italiane

The thesis studies the economic and financial conditions of Italian households, by using microeconomic data of the Survey on Household Income and Wealth (SHIW) over the period 1998-2006. It develops along two lines of enquiry. First it studies the determinants of households holdings of assets and liabilities and estimates their correlation degree. After a review of the literature, it estimates two non-linear multivariate models on the interactions between assets and liabilities with repeated cross-sections. Second, it analyses households financial difficulties. It defines a quantitative measure of financial distress and tests, by means of non-linear dynamic probit models, whether the probability of experiencing financial difficulties is persistent over time. Chapter 1 provides a critical review of the theoretical and empirical literature on the estimation of assets and liabilities holdings, on their interactions and on households net wealth. The review stresses the fact that a large part of the literature explain households debt holdings as a function, among others, of net wealth, an assumption that runs into possible endogeneity problems. Chapter 2 defines two non-linear multivariate models to study the interactions between assets and liabilities held by Italian households. Estimation refers to a pooling of cross-sections of SHIW. The first model is a bivariate tobit that estimates factors affecting assets and liabilities and their degree of correlation with results coherent with theoretical expectations. To tackle the presence of non normality and heteroskedasticity in the error term, generating non consistent tobit estimators, semi-parametric estimates are provided that confirm the results of the tobit model. The second model is a quadrivariate probit on three different assets (safe, risky and real) and total liabilities; the results show the expected patterns of interdependence suggested by theoretical considerations. Chapter 3 reviews the methodologies for estimating non-linear dynamic panel data models, drawing attention to the problems to be dealt with to obtain consistent estimators. Specific attention is given to the initial condition problem raised by the inclusion of the lagged dependent variable in the set of explanatory variables. The advantage of using dynamic panel data models lies in the fact that they allow to simultaneously account for true state dependence, via the lagged variable, and unobserved heterogeneity via individual effects specification. Chapter 4 applies the models reviewed in Chapter 3 to analyse financial difficulties of Italian households, by using information on net wealth as provided in the panel component of the SHIW. The aim is to test whether households persistently experience financial difficulties over time. A thorough discussion is provided of the alternative approaches proposed by the literature (subjective/qualitative indicators versus quantitative indexes) to identify households in financial distress. Households in financial difficulties are identified as those holding amounts of net wealth lower than the value corresponding to the first quartile of net wealth distribution. Estimation is conducted via four different methods: the pooled probit model, the random effects probit model with exogenous initial conditions, the Heckman model and the recently developed Wooldridge model. Results obtained from all estimators accept the null hypothesis of true state dependence and show that, according with the literature, less sophisticated models, namely the pooled and exogenous models, over-estimate such persistence.

NMR, Metabonomics and Molecular Profiles: Applications to the Quality Assessment of Foodstuffs

Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

Spinal cord injury: assessment of autonomic state-dependent control of cardiovascular system and body core temperature

Spinal cord injury (SCI) results not only in paralysis; but it is also associated with a range of autonomic dysregulation that can interfere with cardiovascular, bladder, bowel, temperature, and sexual function. The entity of the autonomic dysfunction is related to the level and severity of injury to descending autonomic (sympathetic) pathways. For many years there was limited awareness of these issues and the attention given to them by the scientific and medical community was scarce. Yet, even if a new system to document the impact of SCI on autonomic function has recently been proposed, the current standard of assessment of SCI (American Spinal Injury Association (ASIA) examination) evaluates motor and sensory pathways, but not severity of injury to autonomic pathways. Beside the severe impact on quality of life, autonomic dysfunction in persons with SCI is associated with increased risk of cardiovascular disease and mortality. Therefore, obtaining information regarding autonomic function in persons with SCI is pivotal and clinical examinations and laboratory evaluations to detect the presence of autonomic dysfunction and quantitate its severity are mandatory. Furthermore, previous studies demonstrated that there is an intimate relationship between the autonomic nervous system and sleep from anatomical, physiological, and neurochemical points of view. Although, even if previous epidemiological studies demonstrated that sleep problems are common in spinal cord injury (SCI), so far only limited polysomnographic (PSG) data are available. Finally, until now, circadian and state dependent autonomic regulation of blood pressure (BP), heart rate (HR) and body core temperature (BcT) were never assessed in SCI patients. Aim of the current study was to establish the association between the autonomic control of the cardiovascular function and thermoregulation, sleep parameters and increased cardiovascular risk in SCI patients.