Bayesian analysis of a Tobit quantile regression model

This paper develops a Bayesian framework for Tobit quantile regression. Our approach is organized around a likelihood function that is based on the asymmetric Laplace dis- tribution, a choice that turns out to be natural in this context. We discuss families of prior distribution on the quantile regression vector that lead to proper posterior distributions with ¯nite moments. We show how the posterior distribution can be sampled and summarized by Markov chain Monte Carlo methods. A method for com- paring alternative quantile regression models is also developed and illustrated. The techniques are illustrated with both simulated and real data. In particular, in an em- pirical comparison, our approach out-performed two other common classical estimators

The Threshold GARCH Model: Estimation and Density Forecasting for Financial Returns*

We consider multiple threshold value-at-risk (VaR$_t$) estimation and density forecasting for financial data following a threshold GARCH model. We develop an $\alpha$-quantile quasi-maximum likelihood estimation (QMLE) method for VaR$_t$ by showing that the associated density function is an $\alpha$-quantile density and belongs to the tick-exponential family. This establishes that our estimator is consistent for the parameters of VaR$_t$. We propose a density forecasting method for quantile models based on VaR$_t$ at a single non-extreme level, which overcomes some limitations of existing forecasting methods with quantile models. We find that for heavy-tailed financial data our $\alpha$-quantile QMLE method for VaR$_t$ outperms the Gaussian QMLE method for volatility. We also find that density forecasts based on VaR$_t$ outperform those based on the volatility of financial data. Empirical work on market returns shows that our approach also outperforms some benchmark models for density forecasting of financial returns

Die bepaling van die ‘sentrum van hoofbelange’ by oorgrens insolvensies: Is die Parmalat-benadering voldoende om die behoeftes van moderne handel te bevredig?

Despite various viewpoints on the determination of the centre of main interest (COMI), the legal question in this investigation is whether, and to what extent, the approach in In re Eurofood IFSC Ltd (the Parmalat case) brings about an effective solution for the determination of the location of the COMI of individual companies, either unattached or as part of a group (in contrast with companies forming a so called economic unit). There exists a presumption that the COMI is situated there where the company’s registered office is. This is the physical factor in determining the COMI. There is also a mental or psychological factor. The COMI must correspond with the place which third parties (including foreigners) regard as the place where the debtor ordinarily manages its business and most prominent interests on a regular basis. If the registered office is situated at one place and the judgment of third parties with regard to the COMI is elsewhere, the presumption will not come into operation and the ordinary onus of proof will rest on the party concerned. If the subsidiary’s registered office and the opinion of third parties point to the same location (in order for the presumption to come into operation) the holding company should lead more substantial evidence so as to rebut the presumption. The presumption shall not be rebutted easily. An essential and delicate process of weighing up relevant factors should take place. The COMI must be identified with reference to criteria which are objectively foreseeable by all parties involved

Epidemiology of acute spinal cord injuries in the Groote Schuur Hospital Acute Spinal Cord Injury (GSH ASCI) Unit, Cape Town, South Africa, over the past 11 years

Background. Spinal cord injury (SCI) is devastating to both patient and society, with acute management and ongoing care being extremely expensive. Few epidemiological data are available on SCIs in South Africa (SA).Objectives. To identify the epidemiological profile of SCI patients at Groote Schuur Hospital (GSH), Cape Town, SA, and identify seasonal trends and peak periods. As the majority of the injuries are preventable, these data are important to develop prevention strategies. Methods. A retrospective review of prospectively collected data was conducted on all patients admitted to the Acute Spinal Cord Injury (ASCI) Unit at GSH from 1 April 2003 to 31 March 2014. All cases registered on a prospectively maintained database were included in the study.Results. The total number of patients admitted to the ASCI Unit was 2 042, with an average of 185 admissions per year. The male/female ratio was 5.25:1. The 21 - 30-year-old age category was the largest, comprising 33.5% of the patients. The most prevalent cause of injury was motor vehicle accidents (44.6%), followed by violence-related injuries (27.2%). Thirty-two point two percent of patients needed ventilatory support, and 91.5% of mechanically ventilated patients were successfully weaned. December was the busiest month in the unit. In patients in whom neurological deficit was incomplete, the average motor function improvement was 16.0%.Conclusions. Data capturing and analysis of SCIs should be encouraged in SA to guide management and prevention strategies, and to optimise outcomes. This study establishes the ASCI Unit at GSH to be one of the key role players in acute SCI management in SA