1,631 research outputs found
On baseline conditions for zero-inflated longitudinal count data
No full textWe describe a mixed-effect hurdle model for zero-inflated longitudinal count data, where a baseline variable is included in the model specification. Association between the count data process and the endogenous baseline variable is modeled through a latent structure, assumed to be dependent across equations. We show how model parameters can be estimated in a finite mixture context, allowing for overdispersion, multivariate association and endogeneity of the baseline variable. The model behavior is investigated through a large-scale simulation experiment. An empirical example on health care utilization data is provided
Joint estimation of conditional quantiles in multivariate linear regression models with an application to financial distress
No full textThis paper proposes a maximum likelihood approach to jointly estimate marginal conditional quantiles of multivariate response variables in a linear regression framework. We consider a slight reparameterization of the multivariate asymmetric Laplace distribution proposed by Kotz et al. (2001) and exploit its location–scale mixture representation to implement a new EM algorithm for estimating model parameters. The idea is to extend the link between the asymmetric Laplace distribution and the well-known univariate quantile regression model to a multivariate context, i.e., when a multivariate dependent variable is concerned. The approach accounts for association among multiple responses and studies how the relationship between responses and explanatory variables can vary across different quantiles of the marginal conditional distribution of the responses. A penalized version of the EM algorithm is also presented to tackle the problem of variable selection. The validity of our approach is analyzed in a simulation study, where we also provide evidence on the efficiency gain of the proposed method compared to estimation obtained by separate univariate quantile regressions. A real data application examines the main determinants of financial distress in a sample of Italian firms
Revisions in official data and forecasting
No full textThis paper deals with the topic of revisions in macroeconomic Italian data with the aim of investigating whether consecutive vintages published by the National Statistical Institute contain useful information for economic analysis and forecasting. The rationality of the revisions process is tested considering the complete history of data and an application to show the usefulness of revisions for improving the precision of forecasts is proposed. The results on Italian GDP show that embedding the revision process in a dynamic factor model helps to reduce the forecast error in the short term
Testing beta-pricing models using large cross-sections
No full textWe propose a methodology for estimating and testing beta-pricing models when a large numberof assets is available for investment but the number of time-series observations is fixed. Wefirst consider the case of correctly specified models with constant risk premia, and then extendour framework to deal with time-varying risk premia, potentially misspecified models, firmcharacteristics, and unbalanced panels. We show that our large cross-sectional framework posesa serious challenge to common empirical findings regarding the validity of beta-pricing models.In the context of pricing models with Fama-French factors, firm characteristics are found toexplain a much larger proportion of variation in estimated expected returns than betas. (JELG12, C12, C52
A biclustering approach to university performances: an Italian case study
No full textUniversity evaluation is a topic of increasing concern in Italy as well as in other countries. In empirical
analysis, university activities and performances are often measured by means of indicator variables. The
available information are then summarized to respond to different aims. We argue that the evaluation
process is a complex phenomenon that cannot be addressed by a simple descriptive approach. In this
paper, we used a model-based approach to account for association between indicators and similarities
among the observed universities. We examine faculty-level data collected from different sources, covering
55 Italian Economics faculties in the academic year 2009/2010. Making use of a clustering methodology,
we introduce a biclustering model that accounts for both homogeneity/heterogeneity among faculties and
correlations between indicators. Our results show that there are two substantial different performances
between universities which can be strictly related to the nature of the institutions, namely the Private
and Public profiles. Each of the two groups has its own peculiar features and its own group-specific list of
priorities, strengths and weaknesses. Thus, we suggest that caution should be used in interpreting standard
university rankings as they generally do not account for the complex structure of the data
Schermi. Immagini, corpi, condivisioni
No full textIn this book the author investigates the digital image proliferation of our times from an interdisciplinary point of view. Starting from the Visual Culture theoretical frame, Valentina Mignano explores the ways in which we interact with the screen, dealing with the "screen experience" in the first years of the network societ
Joint VaR and ES forecasting in a multiple quantile regression framework
No full textAn accurate assessment of tail dependencies of financial returns is key for risk management and portfolio allocation. In this paper we consider a multiple linear quantile regression setting for joint prediction of tail risk measures, namely Value at Risk(Var) and Expected Shortfall (ES) using a generalization of the Multivariare Asymmetric Laplace distribution. The proposed method permits simultaneous modelling of multiple conditional quantiles of a multivariate response variable and allows to study the dependence structure among financial assets at different quantile levels. Subsequently, we introduce an original method for portfolio construction where we show that the portfolio returns follow a univariate asymmetric Laplace density. An empirical application to weekly returns of three stock market indices, namely FTSE 100, NIKKEI 225 and S&P 500, illustrates the practical applicability and relevance of joint estimation of VaR and ES in a multivariate framework
Forecasting Multiple VaR and ES Using a Dynamic Joint Quantile Regression with an Application to Portfolio Optimization
No full textAn accurate assessment of tail dependencies of financial returns is key for risk management and portfolio allocation. The use of quantitative risk measures has become an essential tool providing support for financial and asset management decisions. Extending (Taylor in J Bus Econ Stat 37(1):121–133, 2019, [10]), we propose a novel multivariate framework to simultaneously estimate Value at Risk (VaR) and Expected Shortfall (ES) of multiple financial assets, by jointly modelling their marginal quantiles taking into account for their dependence structure. We generalize the joint quantile regression approach by specifying a Conditional Autoregressive Value at Risk (CAViaR) structure in the dynamics of each marginal quantile and modelling the ES of each asset in a time-varying setting. In addition, we propose a new method for portfolio construction, based on the multivariate structure of the problem. We apply our approach to weekly stock market returns, to illustrate the practical applicability of the proposed method and its efficiency gain compared to the univariate approach
Modalita’ di finanziamento della Assistenza Sanitaria erogata ai pazienti stranieri nelle regioni italiane
No full textConsiderato come manchi all’interno della formula capitaria applicata dalle Regioni un aggiustamento che tenga conto dei bisogni di salute degli immigrati si è cercato di evidenziare brevemente quali siano i criteri attualmente adottati dalle Regioni . In conclusione, da quanto esposto si evince come a livello regionale non sia previsto attualmente un sistema specificamente adottato per finan-ziare la salute della popolazione straniera presente sul territorio nazionale. Saper rispondere ai bisogni delle fasce più deboli dal punto di vista socio-economico è un obiettivo di equità che il sistema sanitario italiano, che as-sume come cardine il principio di equità orizzontale non può non rispettare dal momento che la salute è un diritto universale sancito dalla Costituzione. Si ritiene pertanto che questa prima ricerca possa essere di sostegno all’ipotesi di sviluppare una formula capitaria per l’allocazione delle risorse che tenga conto in maniera specifica dei bisogni di cure degli immigrati, in quanto gli immigrati rappresentano categorie fragili che meritano un uguale accesso per uguale bisogno come contemplato dal principio di equità orizzontale in modo da poter garantire loro il diritto alla salute in maniera non disuguale dai cittadini italiani
ENTREPRENEURSHIP AND FEMALE ENTREPRENEURSHIP IN MARAMURES COUNTY
No full textInitiating and developing a business involves a considerable risk and a sustained effort in order to defeat the inertia against what is new. The person initiating a business, assuming the responsibility and risk of its development and benefiting from theentrepreneurship, female entrepreneurship, profit, businesses
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