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.

Fiber beam-columns models with flexure-shear interaction for nonlinear analysis of reinforced concrete structures

The aim of this study was to develop a model capable to capture the different contributions which characterize the nonlinear behaviour of reinforced concrete structures. In particular, especially for non slender structures, the contribution to the nonlinear deformation due to bending may be not sufficient to determine the structural response. Two different models characterized by a fibre beam-column element are here proposed. These models can reproduce the flexure-shear interaction in the nonlinear range, with the purpose to improve the analysis in shear-critical structures. The first element discussed is based on flexibility formulation which is associated with the Modified Compression Field Theory as material constitutive law. The other model described in this thesis is based on a three-field variational formulation which is associated with a 3D generalized plastic-damage model as constitutive relationship. The first model proposed in this thesis was developed trying to combine a fibre beamcolumn element based on the flexibility formulation with the MCFT theory as constitutive relationship. The flexibility formulation, in fact, seems to be particularly effective for analysis in the nonlinear field. Just the coupling between the fibre element to model the structure and the shear panel to model the individual fibres allows to describe the nonlinear response associated to flexure and shear, and especially their interaction in the nonlinear field. The model was implemented in an original matlab® computer code, for describing the response of generic structures. The simulations carried out allowed to verify the field of working of the model. Comparisons with available experimental results related to reinforced concrete shears wall were performed in order to validate the model. These results are characterized by the peculiarity of distinguishing the different contributions due to flexure and shear separately. The presented simulations were carried out, in particular, for monotonic loading. The model was tested also through numerical comparisons with other computer programs. Finally it was applied for performing a numerical study on the influence of the nonlinear shear response for non slender reinforced concrete (RC) members. Another approach to the problem has been studied during a period of research at the University of California Berkeley. The beam formulation follows the assumptions of the Timoshenko shear beam theory for the displacement field, and uses a three-field variational formulation in the derivation of the element response. A generalized plasticity model is implemented for structural steel and a 3D plastic-damage model is used for the simulation of concrete. The transverse normal stress is used to satisfy the transverse equilibrium equations of at each control section, this criterion is also used for the condensation of degrees of freedom from the 3D constitutive material to a beam element. In this thesis is presented the beam formulation and the constitutive relationships, different analysis and comparisons are still carrying out between the two model presented.

Multidimensional item response theory models with general and specific latent traits for ordinal data

The aim of the thesis is to propose a Bayesian estimation through Markov chain Monte Carlo of multidimensional item response theory models for graded responses with complex structures and correlated traits. In particular, this work focuses on the multiunidimensional and the additive underlying latent structures, considering that the first one is widely used and represents a classical approach in multidimensional item response analysis, while the second one is able to reflect the complexity of real interactions between items and respondents. A simulation study is conducted to evaluate the parameter recovery for the proposed models under different conditions (sample size, test and subtest length, number of response categories, and correlation structure). The results show that the parameter recovery is particularly sensitive to the sample size, due to the model complexity and the high number of parameters to be estimated. For a sufficiently large sample size the parameters of the multiunidimensional and additive graded response models are well reproduced. The results are also affected by the trade-off between the number of items constituting the test and the number of item categories. An application of the proposed models on response data collected to investigate Romagna and San Marino residents' perceptions and attitudes towards the tourism industry is also presented.

An equilibrium approach to modelling social interaction

The aim of this work is to put forward a statistical mechanics theory of social interaction, generalizing econometric discrete choice models. After showing the formal equivalence linking econometric multinomial logit models to equilibrium statical mechanics, a multi- population generalization of the Curie-Weiss model for ferromagnets is considered as a starting point in developing a model capable of describing sudden shifts in aggregate human behaviour. Existence of the thermodynamic limit for the model is shown by an asymptotic sub-additivity method and factorization of correlation functions is proved almost everywhere. The exact solution for the model is provided in the thermodynamical limit by nding converging upper and lower bounds for the system's pressure, and the solution is used to prove an analytic result regarding the number of possible equilibrium states of a two-population system. The work stresses the importance of linking regimes predicted by the model to real phenomena, and to this end it proposes two possible procedures to estimate the model's parameters starting from micro-level data. These are applied to three case studies based on census type data: though these studies are found to be ultimately inconclusive on an empirical level, considerations are drawn that encourage further refinements of the chosen modelling approach, to be considered in future work.

Customer Evolution in Sales Channel Migration

This research has been triggered by an emergent trend in customer behavior: customers have rapidly expanded their channel experiences and preferences beyond traditional channels (such as stores) and they expect the company with which they do business to have a presence on all these channels. This evidence has produced an increasing interest in multichannel customer behavior and it has motivated several researchers to study the customers’ channel choices dynamics in multichannel environment. We study how the consumer decision process for channel choice and response to marketing communications evolves for a cohort of new customers. We assume a newly acquired customer’s decisions are described by a “trial” model, but the customer’s choice process evolves to a “post-trial” model as the customer learns his or her preferences and becomes familiar with the firm’s marketing efforts. The trial and post-trial decision processes are each described by different multinomial logit choice models, and the evolution from the trial to post-trial model is determined by a customer-level geometric distribution that captures the time it takes for the customer to make the transition. We utilize data for a major retailer who sells in three channels – retail store, the Internet, and via catalog. The model is estimated using Bayesian methods that allow for cross-customer heterogeneity. This allows us to have distinct parameters estimates for a trial and an after trial stages and to estimate the quickness of this transit at the individual level. The results show for example that the customer decision process indeed does evolve over time. Customers differ in the duration of the trial period and marketing has a different impact on channel choice in the trial and post-trial stages. Furthermore, we show that some people switch channel decision processes while others don’t and we found that several factors have an impact on the probability to switch decision process. Insights from this study can help managers tailor their marketing communication strategy as customers gain channel choice experience. Managers may also have insights on the timing of the direct marketing communications. They can predict the duration of the trial phase at individual level detecting the customers with a quick, long or even absent trial phase. They can even predict if the customer will change or not his decision process over time, and they can influence the switching process using specific marketing tools

Specification and Verification of Declarative Open Interaction Models - A Logic-based framework

The advent of distributed and heterogeneous systems has laid the foundation for the birth of new architectural paradigms, in which many separated and autonomous entities collaborate and interact to the aim of achieving complex strategic goals, impossible to be accomplished on their own. A non exhaustive list of systems targeted by such paradigms includes Business Process Management, Clinical Guidelines and Careflow Protocols, Service-Oriented and Multi-Agent Systems. It is largely recognized that engineering these systems requires novel modeling techniques. In particular, many authors are claiming that an open, declarative perspective is needed to complement the closed, procedural nature of the state of the art specification languages. For example, the ConDec language has been recently proposed to target the declarative and open specification of Business Processes, overcoming the over-specification and over-constraining issues of classical procedural approaches. On the one hand, the success of such novel modeling languages strongly depends on their usability by non-IT savvy: they must provide an appealing, intuitive graphical front-end. On the other hand, they must be prone to verification, in order to guarantee the trustworthiness and reliability of the developed model, as well as to ensure that the actual executions of the system effectively comply with it. In this dissertation, we claim that Computational Logic is a suitable framework for dealing with the specification, verification, execution, monitoring and analysis of these systems. We propose to adopt an extended version of the ConDec language for specifying interaction models with a declarative, open flavor. We show how all the (extended) ConDec constructs can be automatically translated to the CLIMB Computational Logic-based language, and illustrate how its corresponding reasoning techniques can be successfully exploited to provide support and verification capabilities along the whole life cycle of the targeted systems.

Preclinical neuroblastoma models for a pharmacological study of a new MYCN oncogene inhibitor

Background. Neuroblastoma is the most deadly solid tumor of childhood. In the 25% of cases it is associated with MYCN amplification (MA), resulting in the disregulation of several genes involved in cancer progression, chemotherapy resistance and poor prognosis causing the disregulation of several genes involved in cancer progression and chemotherapy resistance and resulting in a poor prognosis. Moreover, in this contest, therapy-related p53 mutations are frequently found in relapsed cases conferring an even stronger aggressiveness. For this reason, the actual therapy requires new antitumor molecules. Therefore, rapid, accurate, and reproducible preclinical models are needed to evaluate the evolution of the different subtypes and the efficacy of new pharmacological strategies. Procedures. We report the real-time tumorigenesis of MA Neuroblastoma mouse models: transgenic TH-MYCN mice and orthotopic xenograft models with either p53wt or p53mut, by non-invasive micro PET and bioluminescent imaging, respectively. Characterization of MYCN amplification and expression was performed on every collected sample. We tested the efficacy of a new MYCN inhibitor in vitro and in vivo. Results. MicroPET in TH-MYCN mice permitted the identification of Neuroblastoma at an early stage and offered a sensitive method to follow metabolic progression of tumors. The MA orthotopic model harboring multitherapy-related p53 mutations showed a shorter latency and progression and a stronger aggressiveness respect to the p53wt model. The presence of MA and overexpression was confirmed in each model and we saw a better survival in the TH-MYCN homozigous mice treated with the inhibitor. Conclusions. The mouse models obtained show characteristics of non-invasiveness, rapidity and sensitivity that make them suitable for the in vivo preclinical study of MA-NB. In particular, our firstly reported p53mut BLI xenograft orthotopic mouse model offers the possibility to evaluate the role of multitherapy-related p53 mutations and to validate new p53 independent therapies for this highly aggressive Neuroblastoma subtype. Moreover, we have shown potential clinical suitability of an antigene strategy through its cellular and molecular activity, ability to specifically inhibit transcription and in vivo efficacy with no evidence of toxicity.

Numerical models of trench migration for lateral heterogeneous subducting plates

The aim of this Thesis is to investigate the effect of heterogeneities within the subducting plate on the dynamics of subduction. In particular, I study the motion of the trench for oceanic and continental subduction, first, separately, and, then, together in the same system to understand how they interact. The understanding of these features is fundamental to reconstruct the evolution of complex subduction zones, such as the Central Mediterranean. For this purpose, I developed 2D and 3D numerical models of oceanic and continental subduction where the rheological, geometrical and compositional properties of the plates are varied. In these models, the trench and the overriding plate move self-consistently as a function of the dynamics of the system. The effect of continental subduction on trench migration is largely investigated. Results from a parametric study showed that despite different rheological properties of the plates, all models with a uniform continental crust share the same kinematic behaviour: the trench starts to advance once the continent arrives at the subduction zone. Hence, the advancing mode in continental collision scenarios is at least partly driven by an intrinsic feature of the system. Moreover, the presence of a weak lower crust within the continental plate can lead to the occurrence of delamination. Indeed, by changing the viscosity of the lower crust, both delamination and slab detachment can occur. Delamination is favoured by a low viscosity value of the lower crust, because this makes the mechanical decoupling easier between crust and lithospheric mantle. These features are observed both in 2D and 3D models, but the numerical results of the 3D models also showed that the rheology of the continental crust has a very strong effect on the dynamics of the whole system, since it influences not only the continental part of plate but also the oceanic sides.

Multilevel Analysis in Household Survey: An Application to Health Condition Data

The aim of this thesis is to apply multilevel regression model in context of household surveys. Hierarchical structure in this type of data is characterized by many small groups. In last years comparative and multilevel analysis in the field of perceived health have grown in size. The purpose of this thesis is to develop a multilevel analysis with three level of hierarchy for Physical Component Summary outcome to: evaluate magnitude of within and between variance at each level (individual, household and municipality); explore which covariates affect on perceived physical health at each level; compare model-based and design-based approach in order to establish informativeness of sampling design; estimate a quantile regression for hierarchical data. The target population are the Italian residents aged 18 years and older. Our study shows a high degree of homogeneity within level 1 units belonging from the same group, with an intraclass correlation of 27% in a level-2 null model. Almost all variance is explained by level 1 covariates. In fact, in our model the explanatory variables having more impact on the outcome are disability, unable to work, age and chronic diseases (18 pathologies). An additional analysis are performed by using novel procedure of analysis :"Linear Quantile Mixed Model", named "Multilevel Linear Quantile Regression", estimate. This give us the possibility to describe more generally the conditional distribution of the response through the estimation of its quantiles, while accounting for the dependence among the observations. This has represented a great advantage of our models with respect to classic multilevel regression. The median regression with random effects reveals to be more efficient than the mean regression in representation of the outcome central tendency. A more detailed analysis of the conditional distribution of the response on other quantiles highlighted a differential effect of some covariate along the distribution.

Validation of the CFD code NEPTUNE for a full scale simulator for decay heat removal systems with in-pool heat exchangers

In the present work, a multi physics simulation of an innovative safety system for light water nuclear reactor is performed, with the aim to increase the reliability of its main decay heat removal system. The system studied, denoted by the acronym PERSEO (in Pool Energy Removal System for Emergency Operation) is able to remove the decay power from the primary side of the light water nuclear reactor through a heat suppression pool. The experimental facility, located at SIET laboratories (PIACENZA), is an evolution of the Thermal Valve concept where the triggering valve is installed liquid side, on a line connecting two pools at the bottom. During the normal operation, the valve is closed, while in emergency conditions it opens, the heat exchanger is flooded with consequent heat transfer from the primary side to the pool side. In order to verify the correct system behavior during long term accidental transient, two main experimental PERSEO tests are analyzed. For this purpose, a coupling between the mono dimensional system code CATHARE, which reproduces the system scale behavior, with a three-dimensional CFD code NEPTUNE CFD, allowing a full investigation of the pools and the injector, is implemented. The coupling between the two codes is realized through the boundary conditions. In a first analysis, the facility is simulated by the system code CATHARE V2.5 to validate the results with the experimental data. The comparison of the numerical results obtained shows a different void distribution during the boiling conditions inside the heat suppression pool for the two cases of single nodalization and three volume nodalization scheme of the pool. Finaly, to improve the investigation capability of the void distribution inside the pool and the temperature stratification phenomena below the injector, a two and three dimensional CFD models with a simplified geometry of the system are adopted.

Potential Analysis for Hypoelliptic Second Order PDEs with Nonnegative Characteristic Form

In this Thesis we consider a class of second order partial differential operators with non-negative characteristic form and with smooth coefficients. Main assumptions on the relevant operators are hypoellipticity and existence of a well-behaved global fundamental solution. We first make a deep analysis of the L-Green function for arbitrary open sets and of its applications to the Representation Theorems of Riesz-type for L-subharmonic and L-superharmonic functions. Then, we prove an Inverse Mean value Theorem characterizing the superlevel sets of the fundamental solution by means of L-harmonic functions. Furthermore, we establish a Lebesgue-type result showing the role of the mean-integal operator in solving the homogeneus Dirichlet problem related to L in the Perron-Wiener sense. Finally, we compare Perron-Wiener and weak variational solutions of the homogeneous Dirichlet problem, under specific hypothesis on the boundary datum.