Modelli di scoring per il rischio paese

Country risk and sovereign risk are two of the most important topics in risk management. The first part of this work introduces these concepts and shows the differences between them. The following chapters fit linear and ordinal regression models to a data-set with more than 100 countries, where the response variable is an appropriate measure of their creditworthiness. The main purposes are to identify the most relevant explanatory variables and to make predictions for those countries whose response variable is not available. For the second aim it is important to verify that records with missing values are not systematically different from the complete ones: a Little test for the MCAR hypothesis is implemented. About model selection, ad hoc algorithms are used and the theory of reduction, proposed by David Hendry, is also briefly described

Modelli di scoring per il rischio paese

Country risk and sovereign risk are two of the most important topics in risk management. The first part of this work introduces these concepts and shows the differences between them. The following chapters fit linear and ordinal regression models to a data-set with more than 100 countries, where the response variable is an appropriate measure of their creditworthiness. The main purposes are to identify the most relevant explanatory variables and to make predictions for those countries whose response variable is not available. For the second aim it is important to verify that records with missing values are not systematically different from the complete ones: a Little test for the MCAR hypothesis is implemented. About model selection, ad hoc algorithms are used and the theory of reduction, proposed by David Hendry, is also briefly described

Missing data: a unified taxonomy guided by conditional independence

Recent work (Seaman et al., 2013; Mealli & Rubin, 2015) attempts to clarify the not always well-understood difference between realised and everywhere definitions of missing at random (MAR) and missing completely at random. Another branch of the literature (Mohan et al., 2013; Pearl & Mohan, 2013) exploits always-observed covariates to give variable-based definitions of MAR and missing completely at random. In this paper, we develop a unified taxonomy encompassing all approaches. In this taxonomy, the new concept of ‘complementary MAR’ is introduced, and its relationship with the concept of data observed at random is discussed. All relationships among these definitions are analysed and represented graphically. Conditional independence, both at the random variable and at the event level, is the formal language we adopt to connect all these definitions. Our paper covers both the univariate and the multivariate case, where attention is paid to monotone missingness and to the concept of sequential MAR. Specifically, for monotone missingness, we propose a sequential MAR definition that might be more appropriate than both everywhere and variable-based MAR to model dropout in certain contexts

Modelli a Equazioni Strutturali per la Valutazione dell'Esperienza Universitaria nell'Ateneo Fiorentino

Every student who has studied at the University of Florence is supposed to fill in a questionnaire prepared by the interuniversity consortium "Almalaurea". This survey concerns the general quality of the college and makes it possible to express the level of satisfaction about many aspects of the University experience. In this paper we wish to evaluate the relationship between observed variables and latent variables of interest: The structural equation models (SEM) is the methodology which suits best our needs. By means of a SEM we aim at building a model that reproduces the determinants of students’ satisfaction. Like any other statistical tool, the SEM is not suitable for causal analysis. However, under certain assumptions, it turns out that the model employed is an adequate representation of the reality under study

Effect of transport length and genotype on tonic immobility, blood parameters and carcass contamination of free-range reared chickens

The aim of the present study was to investigate the effect of transport on welfare traits, several haematological parameters and carcase hygiene in two different chicken genotypes (fast- and slow-growing strains) reared under free-range conditions. For this aim, two hundred male chicks, 100 from fast-growing (Ross 308, R) and 100 from slow-growing (Naked Neck, NN) strain were farmed. At the end of the rearing period, at 81 days of age, 56 birds/strain were randomly selected for slaughtering and submitted to two different pre-slaughter conditions: no transport (0h) or 4 hours of transport (4h). Tonic immobility (TI), blood parameters and carcase hygiene traits were determined. Strain and transport significantly affected TI of birds. Both experimental factors and their interaction significantly affected plasma creatine kinase, alkaline phosphatase, alanine aminotransferase and aspartate aminotransferase. Cholesterol and triglycerides were not different between the experimental groups, whereas glucose decreased after 4 hours of transport in both strains. A significant difference between groups for the heterophils/lymphocytes ratio after transport was also observed, with NN being higher than Ross. Concerning the oxidative stress, we observed a higher ROS production in NN chickens. The carcase microbial characteristics showed a higher level of contamination after the transport (total viable counts), but not concerning the Enterobacteriaceae counts

The impact of upper motor neuron involvement on clinical features, disease progression and prognosis in amyotrophic lateral sclerosis

ObjectivesIn amyotrophic lateral sclerosis (ALS) both upper (UMNs) and lower motor neurons (LMNs) are involved in the process of neurodegeneration, accounting for the great disease heterogeneity. We evaluated the associations of the burden of UMN impairment, assessed through the Penn Upper Motor Neuron Score (PUMNS), with demographic and clinical features of ALS patients to define the independent role of UMN involvement in generating disease heterogeneity, predicting disease progression and prognosis.MethodsWe collected the following clinical parameters on a cohort of 875 ALS patients: age and site of onset, survival, MRC scale, lower motor neuron score (LMNS), PUMNS, ALSFRS-R, change in ALSFRS-R over time (DFS), MITOS and King’s staging systems (KSS). Transcranial magnetic stimulation was performed on a subgroup of patients and central motor conduction time (CMCT) and cortical silent period (CSP) were calculated.ResultsWe observed that patients with an earlier age at onset and bulbar onset had higher PUMNS values. Higher values were also associated to lower ALSFRS-R and to higher DFS scores, as well as to higher MITOS and KSS, indicating that a greater UMN burden correlates with disease severity. Conversely, we did not appreciate any association between UMN involvement and survival or markers of LMN impairment. Moreover, PUMNS values showed a positive association with CMCT and a negative one with CSP values.InterpretationOur results suggest that the burden of UMN pathology, assessed through PUMNS, has an important independent role in defining clinical characteristics, functional disability, disease progression and prognosis in ALS patients. We also support the role of TMS in defining severity of UMN involvement