1,721,025 research outputs found
Random parameters logit models applied to public transport demand
No full textThe multinomial logit model has been used widely as a fundamental tool for the analysis of discrete choices and has found large application in transport studies. However, its restrictive assumptions, such as independence from irrelevant alternatives (IIA) and preference homogeneity across respondents, have motivated the development of more flexible model structures that allow for an increasingly realistic representation of travel behaviour. Among these, a primary role is played by random parameter models. This paper proposes a comparison between two different specifications of random parameter models, namely the mixed logit and the discrete mixture model. An application to public transport demand is illustrated
L’eterogeneità delle preferenze nel trasporto merci: un confronto tra diversi metodi per catturarla.
No full textLa struttura delle preferenze relative al trasporto merci è generalmente caratterizzata dalla presenza di una forte eterogeneità dovuta alle specifiche caratteristiche della merce trasportata, dell’azienda che commissiona il trasporto, degli operatori che se ne occupano, dell’area in cui il trasporto si sviluppa. La classe dei modelli logit a parametri casuali si prefigge lo scopo di catturare tale eterogeneità e di integrarla nei processi di stima. In questo articolo verranno confrontati diversi modelli all’interno 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 capacità di rappresentare l’eterogeneità, della semplicità di interpretazione dei risultati e delle difficoltà computazionali. Il confronto verrà 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
Testing for positive association in contingency tables with fixed margins
No full textAn exact conditional approach is developed to test for certain forms of positive association
between two ordinal variables (e.g. positive quadrant dependence, total positivity of order 2).
The approach is based on the use of a test statistic measuring the goodness-of-(t of the model
formulated according to the type of positive association of interest. The nuisance parameters, corresponding
to the marginal distributions of the two variables, are eliminated by conditioning the
inference on the observed margins. This, in turn, allows to remove the uncertainty on the conclusion
of the test, which typically arises in the unconditional context where the null distribution of
the test statistic depends on such parameters. Since the multivariate generalized hypergeometric
distribution, which results from conditioning, is normally intractable, Markov chain Monte Carlo
methods are used to obtain maximum likelihood estimates of the parameters of the constrained
model. The Pearson’s chi-squared statistics is used as a test statistic; a p-value forthis statistic
is computed through simulation, when the data are sparse, or exploiting the asymptotic theory
based on the chi-bar squared distribution. The extension of the present approach to deal with
bivariate contingency tables, strati(ed according to one or more explanatory discrete variables,
is also outlined. Finally, three applications based on real data are presented
Can CDS indexes signal future turmoils in the stock market? A Markov switching perspective
No full textSingle-name Credit Default Swaps (CDS) are considered the main providers
of direct information related with a reference entity’s creditworthiness and, for this reason, they have often been the core of news on the current financial crisis. The academic
research has focused mainly on the capacity of CDS in anticipating agencies’ official
rating changes and—in this respect—on their superior signalling power, compared to
bond and stock markets. The aim of this work is, instead, to investigate the ability of
fluctuations in CDS indexes in anticipating the occurrence of stock market crises. Our
goal is to show that CDS indexes may provide investors and institutions with early
warning signals of financial distresses in the stock market. We make use of a Markov
switching model with states characterized by increasing levels of volatility and compare the times in which the first switch in a high volatility state occurs, respectively,
in CDS and stock market index quotes. The data set consists of daily closing quotes
for 5 years CDS and stock market index prices, covering the time period from 2004
to 2010. In order to capture possible geographic differences in CDS index capacity of
foreseeing stock market distresses, data referring to two different regions, Europe and
United States, are analyzed
Bayesian inference for Hidden Markov Models
No full textDipartimento di Istituzioni Economiche e Finanziarie, Università degli Studi di Macerata.
Working Paper 43-200
Correction to: Size‐Dependent Enforcement, Tax Evasion and Dimensional Trap
Full text linkThe article “Size‐Dependent Enforcement, Tax Evasion and Dimensional Trap”, written by Raffaella Coppier, Elisabetta Michetti and Luisa Scaccia, was originally published electronically on the publisher’s internet portal on 05 July 2023 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 24 February 2024 to © The Author(s) 2024 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made
The use of mixtures for dealing with non-normal regression errors
No full textIn 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
CDS and Rating Announcements: changing signaling during the crisis?
No full textIn parallel with the development of credit derivatives market, researchers have begun to explore the relationship between Credit Default Swap (CDS) market and rating events. Many papers, via classical event-study methodology, show that CDS market is able to signal future negative rating events announced by credit rating agencies. In this work, we incorporate into the eventstudy
methodology the ability of Markov switching models in modeling state dependent means and variances. This approach allows to get over the drawbacks of the classical methodology, which ignores the heteroscedasticity and volatility clustering often affecting financial time series. The proposed methodology is applied to study the reactions of CDS quotes to reviews for downgrading and
effective downgradings announced by the three major credit rating agencies (Fitch Ratings, Moody’s, Standard and Poor’s), in order to examine if and to what extent CDS market anticipates announcements related with a company’s creditworthiness.
The analysis, focusing mainly on volatility, is performed on two periods, 2004–2006 and 2007–2009, in order to verify whether a change in the signaling power of CDS quotes can be ascribed to recent financial turmoils
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