L\u2019eterogeneit\ue0 delle preferenze nel trasporto merci: un confronto tra diversi metodi per catturarla.

La struttura delle preferenze relative al trasporto merci \ue8 generalmente caratterizzata dalla presenza di una forte eterogeneit\ue0 dovuta alle specifiche caratteristiche della merce trasportata, dell\u2019azienda che commissiona il trasporto, degli operatori che se ne occupano, dell\u2019area in cui il trasporto si sviluppa. La classe dei modelli logit a parametri casuali si prefigge lo scopo di catturare tale eterogeneit\ue0 e di integrarla nei processi di stima. In questo articolo verranno confrontati diversi modelli all\u2019interno di questa classe. I modelli in esame differiscono per le assunzioni fatte circa la distribuzione dei parametri nella popolazione. In particolare, verranno considerati sia modelli basati su distribuzioni continue che modelli basati su distribuzioni discrete. I modelli saranno confrontati sulla base della loro capacit\ue0 di rappresentare l\u2019eterogeneit\ue0, della semplicit\ue0 di interpretazione dei risultati e delle difficolt\ue0 computazionali. Il confronto verr\ue0 effettuato sulla base di dati derivanti dalle preferenze dichiarate di 51 imprese marchigiane, appartenenti ai settori metallurgico (DJ) e mobile (DN), circa le caratteristiche del loro trasporto merci tipico

A Markov Switching Re-evaluation of Event-Study Methodology

This paper reconsiders event-study methodology in light of evidences showing that Cumulative Abnormal Return (CAR) can result in misleading inferences about financial market efficiency and pre(post)-event behavior. In particular, CAR can be biased downward, due to the increased volatility on the event day and within the event window. We propose the use of Markov Switching Models to capture the effect of an event on security prices. We apply the proposed methodology to a set of 45 historical series on Credit Default Swap (CDS) quotes subject to multiple credit events, such as reviews for downgrading. Since CDSs provide insurance against the default of a particular company or sovereign entity, this study checks if market anticipates reviews for downgrading and evaluates the time period the announcements lag behind the market

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Testing for simplification in spatial models

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Testing for positive association in contingency tables with fixed margins

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In many situations, the distribution of the error terms of a linear regression model departs significantly from normality. It is shown, through a simulation study, that an effective strategy to deal with these situations is fitting a regression model based on the assumption that the error terms follow a mixture of normal distributions. The main advantage, with respect to the usual approach based on the least-squares method is a greater precision of the parameter estimates and confidence intervals. For the parameter estimation we make use of the EM algorithm, while confidence intervals are constructed through a bootstrap method

Bayesian Flexible Modelling of Mixed Logit Models

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Model-based tests for simplification of lattice processes

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