Analisi congiunturale e strutturale delle economie regionali: un approccio "fuzzy" alla specializzazione produttiva

Nel 2009 l'Italia attraversa la più grande crisi economica del secondo dopoguerra. Lo studio di ciò che accade, attraverso uno sguardo attento alle principali variabili congiunturali prodotte nel paese, è fondamentale per capire quali sono state le cause che hanno portato a questa situazione e per dare la possibilità  ai policy maker di limitarne gli effetti in futuro. Ma l'Italia non è un territorio dalle caratteristiche monolitiche, è un aggregato di parti molto diverse fra loro. Analizzando il territorio italiano come insieme delle sue parti, osserveremo le medesime condizioni economiche ripetersi in ogni territorio del paese? L'esperienza ci suggerisce di no. La tesi vuole evidenziare come e quanto la struttura caratteristica del tessuto produttivo regionale è responsabile anche della performance economica. La tesi è quindi caratterizzata da due parti. Da un lato si è cercato di analizzare quali siano le differenze nei cicli economici regionali, dall'altro, attraverso l'utilizzo di un sistema di valutazione "fuzzy", si è cercato di ricostruire la natura strutturale delle regioni, al fine di determinare quali siano le specializzazioni che ogni territorio è in grado di mettere in campo. La tesi si conclude con un'analisi comparativa degli indici di dissimilarità  tra cicli regionali e nazionale e i livelli sintetici di specializzazione, si è verificato che esiste una relazione forte che lega le caratteristiche strutturali delle regioni alle distanze tra i loro cicli, dimostrando quindi la tesi che struttura regionale e performance economica siano strettamente interconnesse.

Quantitative evaluation of household nutrition patterns: an econometric assessment of the UK 5-a-day impact on fruit and vegetable consumption

The present work provides an ex-post assessment of the UK 5-a-day information campaign where the positive effects of information on consumption levels are disentangled from the potentially conflicting price dynamics. A model-based estimate of the counterfactual (no-intervention) scenario is computed using data from the Expenditure and Food Survey between 2002 and 2006. For this purpose fruit and vegetable demand is modelled employing Quadratic Almost Ideal Demand System (QUAIDS) specification with demographic effects and controlling for potential endogeneity of prices and total food expenditure.

Gli effetti degli episodi di disoccupazione sulla durata della ricerca di lavoro. Uno studio sui dati del panel europeo

Nel corso degli ultimi venti anni si è assistito ad un incremento generalizzato della disoccupazione in Europa in particolare di quella giovanile: nel 1997 in molti paesi europei il tasso di disoccupazione della classe 15-24 anni è doppio rispetto a quello degli adulti. Questo lavoro si propone di dare una descrizione realistica del fenomeno della disoccupazione giovanile in Italia come risultante dalle prime 4 waves dell’indagine European Household Community Panel indagando la probabilità di transizione dallo stato di disoccupazione a quello di occupazione. Nell’ambito di un’impostazione legata alla teoria dei processi stocastici e dei dati di durata si indagheranno gli effetti che episodi di disoccupazione precedenti possono avere sulla probabilità di trovare un lavoro, in particolare, nell’ambito di processi stocastici più generali si rilascerà l’ipotesi di semi-markovianità del processo per considerare l’effetto di una funzione della storia passata del processo sulla transizione attuale al lavoro. La stima della funzione di rischio a vari intervalli di durata si dimostra più appropriata quando si tiene conto della storia passata del processo, in particolare, si verifica l’ipotesi che la possibilità di avere successo nella ricerca di un lavoro è negativamente influenzata dall’aver avuto in passato molte transizioni disoccupazione-occupazione-disoccupazione.

Indicatori di correlazione e di disordine basati sul concetto di entropia

The aim of this work is to carry out an applicative, comparative and exhaustive study between several entropy based indicators of independence and correlation. We considered some indicators characterized by a wide and consolidate literature, like mutual information, joint entropy, relative entropy or Kullback Leibler distance, and others, more recently introduced, like Granger, Maasoumi and racine entropy, also called Sρ, or utilized in more restricted domains, like Pincus approximate entropy or ApEn. We studied the behaviour of such indicators applying them to binary series. The series was designed to simulate a wide range of situations in order to characterize indicators limit and capability and to identify, case by case, the more useful and trustworthy ones. Our target was not only to study if such indicators were able to discriminate between dependence and independence because, especially for mutual information and Granger, Maasoumi and Racine, that was already demonstrated and reported in literature, but also to verify if and how they were able to provide information about structure, complexity and disorder of the series they were applied to. Special attention was paid on Pincus approximate entropy, that is said by the author to be able to provide information regarding the level of randomness, regularity and complexity of a series. By means of a focused and extensive research, we furthermore tried to clear the meaning of ApEn applied to a couple of different series. In such situation the indicator is named in literature as cross-ApEn. The cross-ApEn meaning and the interpretation of its results is often not simple nor univocal and the matter is scarcely delved into by literature, thereby users can easily leaded up to a misleading conclusion, especially if the indicator is employed, as often unfortunately it happens, in uncritical manner. In order to plug some cross-ApEn gaps and limits clearly brought out during the experimentation, we developed and applied to the already considered cases a further indicator we called “correspondence index”. The correspondence index is perfectly integrated into the cross-ApEn computational algorithm and it is able to provide, at least for binary data, accurate information about the intensity and the direction of an eventual correlation, even not linear, existing between two different series allowing, in the meanwhile, to detect an eventual condition of independence between the series themselves.

Inference on copula-based correlation structures

We propose an extension of the approach provided by Kluppelberg and Kuhn (2009) for inference on second-order structure moments. As in Kluppelberg and Kuhn (2009) we adopt a copula-based approach instead of assuming normal distribution for the variables, thus relaxing the equality in distribution assumption. A new copula-based estimator for structure moments is investigated. The methodology provided by Kluppelberg and Kuhn (2009) is also extended considering the copulas associated with the family of Eyraud-Farlie-Gumbel-Morgenstern distribution functions (Kotz, Balakrishnan, and Johnson, 2000, Equation 44.73). Finally, a comprehensive simulation study and an application to real financial data are performed in order to compare the different approaches.

An evolutionary approach to the design of experiments for combinatorial optimization with an application to enzyme engineering

In a large number of problems the high dimensionality of the search space, the vast number of variables and the economical constrains limit the ability of classical techniques to reach the optimum of a function, known or unknown. In this thesis we investigate the possibility to combine approaches from advanced statistics and optimization algorithms in such a way to better explore the combinatorial search space and to increase the performance of the approaches. To this purpose we propose two methods: (i) Model Based Ant Colony Design and (ii) Naïve Bayes Ant Colony Optimization. We test the performance of the two proposed solutions on a simulation study and we apply the novel techniques on an appplication in the field of Enzyme Engineering and Design.

Gli esiti scolastici nelle scuole di secondo grado di Bologna: un'applicazione della teoria dei modelli a curva latente

Nella presente analisi si è avuta l’eccezionale disponibilità di dati longitudinali su molti individui (6000studenti frequentanti le scuole superiori bolognesi). Per ottenere un modello che al meglio spiegasse e riproducesse l’andamento degli esiti scolastici (promozione alla classe successiva) tenendo conto del percorso scolastico nel tempo, si è scelto il modello a curva latente condizionato. La variabile risposta è combinazione lineare dell’esito di fine anno (Promosso/Non promosso); riassume, per ogni studente/anno scolastico, classe frequentata ed esito finale. Le variabili esplicative sono state selezionate tra le informazioni disponibili per gli individui. Vengono presentati alcuni dati aggregati, poi descritti i dati individuali che entreranno nel modello, evidenziando la composizione degli studenti. La prima fase è la stima del modello logistico, con specificazione delle criticità, che hanno indotto alla scelta successiva del modello dipendente dal tempo. Dopo la descrizione della metodologia principale utilizzata, la teoria del conditionalLCM, e la selezione degli indicatori di fitting, viene delineata la procedura di stima, e raggiunto il modello ottimale. Le variabili significative per spiegare l’andamento delle promozioni individuali nel tempo risultano: cittadinanza (italiani con risultati significativamente migliori degli stranieri), sesso (ragazze con percorso scolastico mediamente migliore dei ragazzi: la differenza risulta però significativa soltanto negli istituti tecnici e professionali), tipologia di scuola frequentata (studenti del liceo con risultati significativamente migliori di chi frequenta altri tipi di istituto). I risultati risultano fortemente dipendenti dai dati impiegati, specie riguardo al limite territoriale. Precedenti analisi evidenziavano una forte differenziazione dei risultati scolastici tra studenti del nord e del sud Italia, oltre che tra studenti dei comuni maggiormente popolati e studenti dei comuni di provincia. Sarebbe interessante disporre di dati individuali analoghi a quelli qui utilizzati, ma riferiti all’intero territorio nazionale, oppure ad un zona maggiormente vasta dell’Italia, onde saggiare l’entità dell’influenza sul percorso scolastico,ed in particolare sulla regolarità, della differenza territoriale.

Le strategie di internazionalizzazione delle imprese distrettuali: un'analisi comparata di tre diversi sistemi locali di produzione in Emilia Romagna

Since the Nineties, the process of globalization has caused a sharp increase in the real and financial integration of the worldwide economy, reducing the obstacles to international trade and minimizing the cost of transaction. The entrance of foreign firms in the domestic market has deeply modified the competitive situation of Italian enterprises, which have been forced to change their strategies in order to cope with those of the new competitors. In this scenario, internationalization is no longer one of the different strategic options available for the firm, but it becomes a forced choice to maintain or acquire a competitive advantage sustainable over time. Internationalization strategies of SMEs, however, are hindered by the shortage of financial resources and entrepreneurial skills, therefore this kind of firms tends toward light forms of foreign expansion, like export and subcontracting. Despite this, many studies have demonstrated that the district localisation increases the firms’ productivity and innovative capacity, so their competiveness both at a domestic and international level. The majority of these empirical contributions has focused mainly on the analysis of commercial flows, confirming that district enterprises reach a superior international performance compared to their external competitors. On the contrary, only few works have tried to evaluate the existence of a district effect on the firms’ ability to invest abroad, but the obtained results are not straightforward. One of the reason of these conclusions is that the phenomena has been analysed without taking into account the differences existing between districts in terms of enterprises’ dimension, diffusion of industrial groups and, above all, the sector of productive specialization, because the technological content of production could improve the innovativeness of district firms, allowing them to adopt advanced forms of internationalisation as foreign direct investments (FDI). The aim of the thesis is to further investigate the district effect on internationalisation, trough an econometric analysis of the international strategies carried out by firms localised in three different local system of production characterised by different technological specialization.

Determinants of child undernutrition in India. A micro-case study to operationalize the Capability Approach

The present research aims at shedding light on the demanding puzzle characterizing the issue of child undernutrition in India. Indeed, the so called ‘Indian development paradox’ identifies the phenomenon according to which higher level of income per capita is recorded alongside a lethargic reduction in the proportion of underweight children aged below three years. Thus, in the time period occurring from 2000 to 2005, real Gross Domestic Production per capita has annually grown at 5.4%, whereas the proportion of children who are underweight has declined from 47% to 46%, a mere one point percent. Such trend opens up the space for discussing the traditionally assumed linkage between income-poverty and undernutrition as well as food intervention as the main focus of policies designed to fight child hunger. Also, it unlocks doors for evaluating the role of an alternative economic approach aiming at explaining undernutrition, such as the Capability Approach. The Capability Approach argues for widening the informational basis to account not only for resources, but also for variables related to liberties, opportunities and autonomy in pursuing what individuals value.The econometric analysis highlights the relevance of including behavioral factors when explaining child undernutrition. In particular, the ability of the mother to move freely in the community without the need of asking permission to her husband or mother-in-law is statistically significant when included in the model, which accounts also for confounding traditional variables, such as economic wealth and food security. Also, focusing on agency, results indicates the necessity of measuring autonomy in different domains and the need of improving the measurement scale for agency data, especially with regards the domain of household duties. Finally, future research is required to investigate policy venues for increasing agency in women and in the communities they live in as viable strategy for reducing the plague of child undernutrition in India.

Identificazione dei fenotipi clinici dell’insufficienza renale cronica che predicono la progressione della malattia. Un’applicazione della tecnica degli alberi decisionali

The primary aim of this dissertation to identify subgroups of patients with chronic kidney disease (CKD) who have a differential risk of progression of illness and the secondary aim is compare 2 equations to estimate the glomerular filtration rate (GFR). To this purpose, the PIRP (Prevention of Progressive Kidney Disease) registry was linked with the dialysis and mortality registries. The outcome of interest is the mean annual variation of GFR, estimated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. A decision tree model was used to subtype CKD patients, based on the non-parametric procedure CHAID (Chi-squared Automatic Interaction Detector). The independent variables of the model include gender, age, diabetes, hypertension, cardiac diseases, body mass index, baseline serum creatinine, haemoglobin, proteinuria, LDL cholesterol, tryglycerides, serum phoshates, glycemia, parathyroid hormone and uricemia. The decision tree model classified patients into 10 terminal nodes using 6 variables (gender, age, proteinuria, diabetes, serum phosphates and ischemic cardiac disease) that predict a differential progression of kidney disease. Specifically, age <=53 year, male gender, proteinuria, diabetes and serum phosphates >3.70 mg/dl predict a faster decrease of GFR, while ischemic cardiac disease predicts a slower decrease. The comparison between GFR estimates obtained using MDRD4 and CKD-EPI equations shows a high percentage agreement (>90%), with modest discrepancies for high and low age and serum creatinine levels. The study results underscore the need for a tight follow-up schedule in patients with age <53, and of patients aged 54 to 67 with diabetes, to try to slow down the progression of the disease. The result also emphasize the effective management of patients aged>67, in whom the estimated decrease in glomerular filtration rate corresponds with the physiological decrease observed in the absence of kidney disease, except for the subgroup of patients with proteinuria, in whom the GFR decline is more pronounced.

Econometric models of financial risks

The goal of this dissertation is to use statistical tools to analyze specific financial risks that have played dominant roles in the US financial crisis of 2008-2009. The first risk relates to the level of aggregate stress in the financial markets. I estimate the impact of financial stress on economic activity and monetary policy using structural VAR analysis. The second set of risks concerns the US housing market. There are in fact two prominent risks associated with a US mortgage, as borrowers can both prepay or default on a mortgage. I test the existence of unobservable heterogeneity in the borrower's decision to default or prepay on his mortgage by estimating a multinomial logit model with borrower-specific random coefficients.

A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

Comparing Different Approaches for Clustering Categorical Data

There are different ways to do cluster analysis of categorical data in the literature and the choice among them is strongly related to the aim of the researcher, if we do not take into account time and economical constraints. Main approaches for clustering are usually distinguished into model-based and distance-based methods: the former assume that objects belonging to the same class are similar in the sense that their observed values come from the same probability distribution, whose parameters are unknown and need to be estimated; the latter evaluate distances among objects by a defined dissimilarity measure and, basing on it, allocate units to the closest group. In clustering, one may be interested in the classification of similar objects into groups, and one may be interested in finding observations that come from the same true homogeneous distribution. But do both of these aims lead to the same clustering? And how good are clustering methods designed to fulfil one of these aims in terms of the other? In order to answer, two approaches, namely a latent class model (mixture of multinomial distributions) and a partition around medoids one, are evaluated and compared by Adjusted Rand Index, Average Silhouette Width and Pearson-Gamma indexes in a fairly wide simulation study. Simulation outcomes are plotted in bi-dimensional graphs via Multidimensional Scaling; size of points is proportional to the number of points that overlap and different colours are used according to the cluster membership.

A moment symbolic representation of Lévy processes with applications

By using a symbolic method, known in the literature as the classical umbral calculus, a symbolic representation of Lévy processes is given and a new family of time-space harmonic polynomials with respect to such processes, which includes and generalizes the exponential complete Bell polynomials, is introduced. The usefulness of time-space harmonic polynomials with respect to Lévy processes is that it is a martingale the stochastic process obtained by replacing the indeterminate x of the polynomials with a Lévy process, whereas the Lévy process does not necessarily have this property. Therefore to find such polynomials could be particularly meaningful for applications. This new family includes Hermite polynomials, time-space harmonic with respect to Brownian motion, Poisson-Charlier polynomials with respect to Poisson processes, Laguerre and actuarial polynomials with respect to Gamma processes , Meixner polynomials of the first kind with respect to Pascal processes, Euler, Bernoulli, Krawtchuk, and pseudo-Narumi polynomials with respect to suitable random walks. The role played by cumulants is stressed and brought to the light, either in the symbolic representation of Lévy processes and their infinite divisibility property, either in the generalization, via umbral Kailath-Segall formula, of the well-known formulae giving elementary symmetric polynomials in terms of power sum symmetric polynomials. The expression of the family of time-space harmonic polynomials here introduced has some connections with the so-called moment representation of various families of multivariate polynomials. Such moment representation has been studied here for the first time in connection with the time-space harmonic property with respect to suitable symbolic multivariate Lévy processes. In particular, multivariate Hermite polynomials and their properties have been studied in connection with a symbolic version of the multivariate Brownian motion, while multivariate Bernoulli and Euler polynomials are represented as powers of multivariate polynomials which are time-space harmonic with respect to suitable multivariate Lévy processes.

Valutazione dei disturbi cognitivi nei pazienti sottoposti a Rivascolarizzazione Carotidea (Endoarterectomia vs Stenting) mediante dosaggio di marker di danno neuronale, Mini Mental State Examination e Risonanza Magnetica

Scopo del nostro studio è quello di valutare i disturbi cognitivi in relazione al tasso di microembolia cerebrale in due gruppi di pazienti trattati per lesione carotidea asintomatica con endoarterectomia (CEA) o stenting (CAS). Comparando le due metodiche mediante l’utilizzo di risonanza magnetica in diffusione (DW-MRI), neuromarkers (NSE e S100β) e test neuropsicometrici. MATERIALE E METODI: 60 pazienti sono stati sottoposti a rivascolarizzazione carotidea (CEA n=32 e CAS n=28). Sono stati tutti valutati con DW-MRI e Mini-Mental State Examination (MMSE) test nel preoperatorio, a 24 ore, a 6 ed a 12 mesi dall’intervento. In tutti sono stati dosati i livelli sierici di NSE e S100β mediante 5 prelievi seriati nel tempo, quello basale nel preoperatorio, l’ultimo a 24 ore. L’ananlisi statistica è stata effettuata con test t di Student per confronti multipli per valori continui e con test χ2 quadro e Fisher per le variabili categoriche. Significatività P <0,05. RISULTATI: Non vi è stato alcun decesso. Un paziente del gruppo CAS ha presentato un ictus ischemico. In 6 pazienti CAS ed in 1 paziente CEA si sono osservate nuove lesioni subcliniche alla RMN-DWI post-operatoria (21,4% vs 3% p=0,03). Nel gruppo CAS le nuove lesioni presenti alla RMN sono risultate significativamente associate ad un declino del punteggio del MMSE (p=0,001). L’analisi dei livelli di NSE e S100β ha mostrato un significativo aumento a 24 ore nei pazienti CAS (P = .02). A 12 mesi i pazienti che avevano presentato nuove lesioni ischemiche nel post-operatorio hanno mostrato minor punteggio al MMSE, non statisticamente significativo. CONCLUSIONI: I neuromarkers in combinazione con MMSE e RMN-DWI possono essere utilizzati nella valutazione del declino cognitivo correlato a lesioni silenti nell’immediato postoperatorio di rivascolarizzazione carotidea. Quest’ultime dovrebbero essere valutate quindi non solo rispetto al tasso di mortalità e ictus, ma anche rispetto al tasso di microembolia.