Celiac disease is an autoimmune disease for which the only treatment is a strictly gluten free diet. Prices of gluten free products are higher than common grain-based food. A consumer who must eat only gluten free products can't choose the price he prefers and faces higher prices. The aim of this research is to evaluate the economic impact associated with the higher prices faced by consumers who receive a celiac disease diagnosis. A protocol to collecting price data on gluten and gluten free products was defined. Following the guidelines specified in the data collection proto- col, gluten and gluten free prices were collected considering the on-line shops of the four most important UK supermarkets, and considering all products potentially containing gluten. The resulting dataset allows us to describe the current situation of gluten free food supply both in terms of the range of available product by category and the corresponding prices. Using the 2012 Living Cost and Food Survey data, an Almost Ideal Demand System was estimate. The estimations of the AIDS provide the key informations needed for the evaluation of the impact of coeliac disease. In practice, we consider the price gap between gluten-free foods and foods containing gluten as an implicit tax. The resulting welfare loss of the celiac consumers was then estimated using compensating variation, based on the AIDS coeficients estimated in the previous step and the collected price data. Hence, we estimate the additional amount of food expenditure which is needed by a celiac consumer to reach the same utility level of a consumer whose choice is not restricted to gluten-free products. Demand and welfare analysis was conducted both for the total population and for three different income brackets, in order to explore the relative impact and potential inequalities across income groups.

This thesis proposes an original interpretative key to a crucial problem of business travel: minimizing the flights cost, managing change and cancellation risk, choosing the optimal fare. Hitherto this topic was addressed only with reference to the revenue management of airlines, possibly because getting the information needed to model the traveler’s behavior, which, as highlighted by a qualitative study, is determined by one-off events, private life and business snags, is nearly impossible. Given that available data, collected by a travel management company for other purposes, concern mainly the tickets and flights’ characteristics, the results obtained in this work are very satisfying. For coping with the informative limitations, some original solutions were developed. First, as the literature suggests a seasonal pattern, tied to vacations, an attempt was made to insert a guess, for a vacation effect, not precise enough to be exploited within a Bayesian framework, directly in estimated models. This improved all the models’ predicting capability, but the value of a business-specific loss function, to assess predictors economically, was disappointing. Therefore, a new classification algorithm, amplifying faint signals, exploiting the whole matrix of estimated probabilities, for each prediction, was conceived. It is very flexible, as it can be applied to any matrix of probabilities, estimated by any classifier, and very effective. In fact, it improved the predictive performance of all the predictors and yielded an estimated global gain of 109,011 euros. Finally, a problem for selecting the best models for two nodes emerged, as all the candidates displayed identical forecasting performance, as assessed through the traditional measures for nominal data, based only on the predicted outcomes. Thus, a Predictive Accuracy Score is elaborated, for evaluating estimated probabilities, which are important, because, when the cost data is available, the expected value of the flights cost will be computable.

In the last decades, evaluation has become an essential tool for policymakers, because it provides unbiased estimates of a policy effect. The purpose of an evaluation is to explore the causal relationship between the implementation of a policy and its effects – the “impact”. In the programming period 2007-2013, the European Commission – and the member States of the EU – have focused their attention on the development of innovation policies within Regional Innovation Systems: for this reason, the innovation policies have been particularly involved in evaluation processes. Six Italian regions have created the Poli di innovazione (Innovation poles), networks of universities, services centres, incubators, public and private laboratories, and enterprises, whose goals are to foster the creation of networks and to stimulate firms’ economic performance through the support in R&D activities. Due to the novelty of the policy, this research is a first attempt to evaluate the Poles, using the Tuscan context as case study. Tuscany Region have supported the creation of twelve poles, facilitating the access to a call for tender for the purchase of R&D qualified services. Using matching and difference-in-differences methods, it has been estimated the Average Treatment on the Treated – in terms of Total Factor Productivity and Labor Productivity – for three possible cases: subsidized SME, SME members of the Poles, subsidized SME members of the Poles. In addition, it has been implemented a model that include network centrality measures to assess the effect of the Poles on the performance of the firms. It emerges that the subsidized firms which belong to the poles experience on average a productivity gain towards the end of the period of subsidization, and the centrality of their pole have a positive effect, which is particularly relevant for the top enterprises – in terms of productivity.

Scegliere di consumare in modo sostenibile significa passare ad un nuovo modello di consumo. Tale modello richiede una maggiore consapevolezza e responsabilità da parte dei consumatori, unite all'adozione di nuovi stili di vita e di scelte d’acquisto, che permettano il raggiungimento di elevati livelli di benessere nel rispetto dell'ambiente. Un notevole sforzo è stato compiuto recentemente dai policy maker per incoraggiare il consumo sostenibile quali implementazioni dello sviluppo sostenibile. Ancora lunga, tuttavia, è la strada da percorrere per raggiungere pienamente questo obiettivo. Tra i prodotti sostenibili, il biologico si è rivelato di gran lunga il più rappresentativo: le statistiche di questo mercato mostrano, infatti, tendenze positive, sebbene il consumo risulti ancora eterogeneo e contenuto rispetto al consumo di alimenti convenzionali. Ciò mostra che il comportamento dei consumatori non è ancora abbastanza reattivo alle suddette politiche. Il presente studio si propone di contribuire alla ricerca sul consumo sostenibile approfondendo i fattori che incoraggiano o impediscono il consumo di prodotti alimentari biologici in Italia. Adottando un nuovo approccio si cerca di capire come i diversi segmenti di diete alimentari affrontino gli alimenti biologici in termini di consumi e di atteggiamenti. Un'analisi multivariata a più fasi è stata condotta su un campione di 3.004 consumatori. Un’analisi delle componenti principali non lineare è stata applicata alle variabili ordinali che misurano il consumo di ventuno categorie di alimenti. Successivamente è stata applicata la cluster analysis che ha dato luogo a quattro segmenti di abitudini alimentari. I prodotti biologici sono diventati parte delle abitudini alimentari in Italia in quasi un terzo della popolazione. Il consumo sembra essersi affermato soprattutto nel segmento con abitudini alimentari sane. Una scarsa attenzione ad una dieta sana, gli stili di vita, il reddito, l'accessibilità, la mancanza di consapevolezza condizionano le abitudini alimentari a scapito di un consumo più sostenibile. / Choosing a sustainable consumption means shifting to a new consumer pattern. It requires greater awareness and responsibility from the consumer side, with the adoption of new lifestyles and purchasing choices enabling to achieve high levels of well-being and satisfaction while respecting the environment. A great effort has been made in last three decades by policy makers worldwide to encouraging sustainable production and consumption putting in practice the sustainable development principles. Still a long way is needed to achieve this objective. Organic food is one of the most representative sustainable product. World and European organic food market statistics highlight positive trends, although consumption results heterogeneous and low compared to conventional food consumption. This implies that consumer behavior is still not sufficiently responsive to policies on sustainable consumption. The present study aims to contribute to extant research on sustainable consumption investigating the factors that encourage or prevent consumption of organic food products. Adopting a new approach it tries to understand how different food diet segments face organic food in term of consumption and attitudes. A multi-step multivariate analysis was carried out on an Italian consumer survey on 3,004 respondents. A nonlinear principal component analysis was applied to variables measuring consumption frequencies for 16 food categories and 5 beverage categories measured on an ordinal scale. In a second step a two stages cluster analysis application provided four food habit segments. Organic products have become part of the eating habits in Italy in almost a third of the population. The consumption seems to be developed mostly in a segment also pursuing healthy eating habits. Low level of attention to a healthy diet, lifestyles, income level, accessibility, a lack of awareness of sustainability condition food habits to the detriment of more sustainable consumption.

Una stampa libera e plurale è un elemento fondante di ogni sistema democratico ed è fondamentale per la creazione di un’opinione pubblica informata e in grado di esercitare controllo e pressione sulle classi dirigenti. Dal momento della loro creazione i giornali si sono imposti come un’importantissima fonte di informazione per l’opinione pubblica. La seconda metà del Novecento, inoltre, ha conosciuto innovazioni tecnologiche che hanno portato grandi cambiamenti nel ruolo della carta stampata come veicolo di trasmissione delle notizie. Partendo dalla diffusione della televisione fino ad arrivare alla rivoluzione digitale degli anni ’90 e 2000, la velocità di creazione e di trasmissione delle informazioni è aumentata esponenzialmente, i costi di produzione e di acquisizione delle notizie sono crollati e una quantità enorme di dati, che possono fornire moltissime informazioni relative alle idee e ai contenuti proposti dai diversi autori nel corso del tempo, è ora a disposizione di lettori e ricercatori. Tuttavia, anche se grazie alla rivoluzione digitale i costi materiali dei periodici si sono notevolmente ridotti, la produzione di notizie comporta altre spese e pertanto si inserisce in un contesto di mercato, sottoposto alle logiche della domanda e dell'offerta. In questo lavoro verrà analizzato il ruolo della domanda e della non perfetta razionalità dei lettori nel mercato delle notizie, partendo dall’assunto che la differenza di opinioni dei consumatori spinge le testate a regolare l’offerta di contenuti, per venire incontro alla domanda di mercato, per verificare l’applicabilità del modello utilizzato (Mullainhatan e Shleifer, 2005) al contesto italiano. A tale scopo si è analizzato il comportamento di alcuni quotidiani nazionali in occasione di due eventi che hanno profondamente interessato l'opinione pubblica italiana: il fenomeno dei flussi migratori provenienti dalla sponda sud del Mediterraneo nel mese di ottobre 2013 e l'epidemia di influenza H1N1 del 2009. / A free and plural press is a central element of every democratic society and is crucial for the development of an informed public opinion, which can control and address the ruling classes. Since their creation, newspapers have been a very important source of information for the public opinion. From the second half of the twentieth century, moreover, several technological revolutions have modified the role of the press as a vehicle for the circulations of news. From the diffusion of the television to the digital revolution of the last two decades, creation and reporting of news has increased exponentially, and a huge quantity of data is now available to readers and researchers. Although the digital revolution has drastically reduced the material costs of news production, publishing companies have to face many other types of cost. This is the reason why this the production and the distribution of news are characterized by market processes and consequently by supply and demand driving forces. Aim of this work is to study the role of the demand and of the bounded rationality of readers, which are especially interested in news consistent with their beliefs. The model of market for news considered (Mullainhatal and Shleifer, 2005) is based on the idea that the differences between readers opinions lead mass-media to diversify their offer of news and to assume positions that can be even more radical than the readers’ ones. To verify the validity of the model for the Italian market for news, the behaviour of some important newspaper has been studied. The articles that have been analysed concerned two events that had a strong impact on the Italian public: the management of migratory flows coming from Northern-African countries during the month of October 2013 and the endemic spread of H1N1 flu (swine flu) in 2009.

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This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

The intensity of regional specialization in specific activities, and conversely, the level of industrial concentration in specific locations, has been used as a complementary evidence for the existence and significance of externalities. Additionally, economists have mainly focused the debate on disentangling the sources of specialization and concentration processes according to three vectors: natural advantages, internal, and external scale economies. The arbitrariness of partitions plays a key role in capturing these effects, while the selection of the partition would have to reflect the actual characteristics of the economy. Thus, the identification of spatial boundaries to measure specialization becomes critical, since most likely the model will be adapted to different scales of distance, and be influenced by different types of externalities or economies of agglomeration, which are based on the mechanisms of interaction with particular requirements of spatial proximity. This work is based on the analysis of the spatial aspect of economic specialization supported by the manufacturing industry case. The main objective is to propose, for discrete and continuous space: i) a measure of global specialization; ii) a local disaggregation of the global measure; and iii) a spatial clustering method for the identification of specialized agglomerations.