1,721,089 research outputs found
A discrete- time hazard model for loans: some evidence from Italian Banking System
No full textProblem statement: The probability of default, PD, is a crucial problem for banks. In the last years international accords (Basel, Basel 2 and Basel 3) have incentived banks to adopt objectives systems to evaluating and monitoring risk of default in order to predict PD for new loans based on borrower's characteristics. The aim of this study is to introduce a discrete survival model to study the risk of default and to propose the empirical evidence by the Italian banking system. Approach: Survival analysis is used if we are interested in whether and when an event occurs. In this context the event occurrence represents a borrower's transition from one state, loan in bonis that is not in default, to another state, the default. In this study through a survival model (in particular a discrete-time hazard model) it is possible verify when the probability of default is the highest considering, for each group of loans, a set of explanatory variables as risk factors of PD. Results: The empirical application obtained through a discrete time hazard model have provided clear evidence that time when the default occurs is an important element to predict the probability of default in time. Regarding Italian data the hazard model shows that explanatory variables (i.e., territorial area, productive economic sector, size of loan and generation of belonging) have effects both on if and on when loan bankrupts. Conclusion: The hazard model estimated for a population of loans involve different probability of default considering conjointly the explanatory variables and the time when the default occurs. Considering jointly the time and the risk factors a probability of default has been modelled for two main groups of loans: "Good borrowers" for which the risk of default is the lowest and "bad borrowers" for which this risk is the highest
Measuring territory student-attractiveness in Italy. Longitudinal evidence
No full textThe aim of this paper is to investigate the factors affecting university student mobility in Italy in a longitudinal perspective, by considering the flows across competing territorial areas supplying tertiary education programs. The Bradley-Terry modelling approach based on pair comparisons has been adopted to define the attractiveness of competing territories and a range of determinants related to the socio-economic characteristics of the areas as well as universities’ resources. Data released by the Italian Ministry of Education (MiUR) are analysed for the academic years 2010/2011-2014/2015. The modelling approach considers score values for each territory and year, allowing to evaluate whether attractiveness improves or deteriorates over time, and to rank areas according to their attractiveness. To this end, an index based on ranking changes, appropriately weighed with the differences in score values, is proposed. Empirical findings highlight that attractiveness depends not only on the educational programs, but also on territories’ socio-economic factors, reflecting the well-known North-South divide that persists in time
Assessment of subjective economic well-being in Italy
No full textUsing the European Survey on Income and Living Conditions for the year
2005, we analyze the subjective economic well-being and its determinants relating to
some sub-groups of Italian households by means of an Ordered Logit Model (OLM),
whose dependent variable is represented by a perception variable, that is the ability of
households to make ends meet. The empirical results highlight that the main
determinants of subjective economic well-being are the same for the four typologies of
households. The subjective economic well-being is not only related to the economic
status, but it is mostly influenced by socio-demographic variables, as work and
education conditions. Furthermore, the level of subjective well-being of Italian
households changes passing from a specific status of socio-demographic variable to
another one
Student background determinants of reading achievement in Italy. A quantile regression analysis
Full text linkIn recent years determinants of students’ achievement has received much attention. Empirical studies
have found that students’ characteristics, family background, school attended, and regional residence are
major factors affecting student performance. In this paper, we analyze the 2009 OECD-PISA (spell PISA)
survey to examine individual background characteristics influencing the reading achievement of Italian
15 years-old students using the quantile regression (QR) approach. The QR approach allows researchers
to analyze changes in size and direction of predictor estimates on student performance across the entire
distribution of reading achievement scores. Results indicate significant effects of predictors on reading
achievement operating differently across quantiles, suggesting different pathways to achievement for
low and high performing readers. In particular, some family background predictors (parental education,
computer availability at home, and availability of a desk for homework at home), the school program
attended and, the region of student residence play important but differing role for low and high
performing readers. For example, parental education shows a positive effect on student reading,
academic (general) programs perform better than vocational or technical, and Northern regions perform
better than Center-Southern ones, with differentiated effects along the distribution of students’ reading
scores. These findings should be carefully considered by policymakers when outlining strategies to
enhance student performance at all levels along the reading continuum of low and high scores
PROFILI DI RISCHIO DEI CREDITI BANCARI ITALIANI: UN'ANALISI PER GENERAZIONI DI FINANZIAMENTI
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