A Consistent Nonparametric Test for Causality in Quantile

This paper proposes a nonparametric test of causality in quantile. Zheng (1998) has proposed an idea to reduce the problem of testing a quantile restriction to a problem of testing a particular type of mean restriction in independent data. We extend Zheng’s approach to the case of dependent data, particularly to the test of Granger causality in quantile. The proposed test statistic is shown to have a second-order degenerate U-statistic as a leading term under the null hypothesis. Using the result on the asymptotic normal distribution for a general second order degenerate U-statistics with weakly dependent data of Fan and Li (1996), we establish the asymptotic distribution of the test statistic for causality in quantile under ß-mixing (absolutely regular) process.Granger Causality, Quantile, Nonparametric Test

On the impact of digital music distribution

We present a framework to evaluate the impact of digital music distribution. We set up a representative model that enables the comparative static analysis. We then interpret two empirical observations about the music industry, the sales decline and the price constancy, and fit the model to these observations. We find that, while the impact of digitalization on the producers' profits is probably negative, it may not be as severe as the observed impact on the quantity. On the other hand, the impact of digitalization on the consumer surplus is unambiguously positive. The impact on the social welfare is rather ambiguous, but numerical calculations reveal that the social welfare has increased for most parameter values. We also show that enhanced copyright protection to counteract the impacts of digitalization may have an unexpected effect on the social welfare.Music industry, Digital music, Copyright, File sharing

Support Vector Regression Based GARCH Model with Application to Forecasting Volatility of Financial Returns

In recent years, support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a moving average (MA), a recurrent NN and a parametric GACH in terms of their ability to forecast financial markets volatility. The real data in this study uses British Pound-US Dollar (GBP) daily exchange rates from July 2, 2003 to June 30, 2005 and New York Stock Exchange (NYSE) daily composite index from July 3, 2003 to June 30, 2005. The experiment shows that, under both varying and fixed forecasting schemes, the SVR-based GARCH outperforms the MA, the recurrent NN and the parametric GARCH based on the criteria of mean absolute error (MAE) and directional accuracy (DA). No structured way being available to choose the free parameters of SVR, the sensitivity of performance is also examined to the free parameters.recurrent support vector regression, GARCH model, volatility forecasting

Highly Variable Genomic Landscape of Endogenous Retroviruses in the C57BL/6J Inbred Strain, Depending on Individual Mouse, Gender, Organ Type, and Organ Location.

Transposable repetitive elements, named the "TREome," represent ~40% of the mouse genome. We postulate that the germ line genome undergoes temporal and spatial diversification into somatic genomes in conjunction with the TREome activity. C57BL/6J inbred mice were subjected to genomic landscape analyses using a TREome probe from murine leukemia virus-type endogenous retroviruses (MLV-ERVs). None shared the same MLV-ERV landscape within each comparison group: (1) sperm and 18 tissues from one mouse, (2) six brain compartments from two females, (3) spleen and thymus samples from four age groups, (4) three spatial tissue sets from two females, and (5) kidney and liver samples from three females and three males. Interestingly, males had more genomic MLV-ERV copies than females; moreover, only in the males, the kidneys had higher MLV-ERV copies than the livers. Perhaps, the mouse-, gender-, and tissue/cell-dependent MLV-ERV landscapes are linked to the individual-specific and dynamic phenotypes of the C57BL/6J inbred population

A novel human glucocorticoid receptor SNP results in increased transactivation potential.

Glucocorticoids are one of the most widely used therapeutics in the treatment of a variety of inflammatory disorders. However, it is known that there are variable patient responses to glucocorticoid treatment; there are responders and non-responders, or those that need higher dosages. Polymorphisms in the glucocorticoid receptor (GR) have been implicated in this variability. In this study, ninety-seven volunteers were surveyed for polymorphisms in the human GR-alpha (hGRα), the accepted biologically active reference isoform. One isoform identified in our survey, named hGR DL-2, had four single nucleotide polymorphisms (SNPs), one synonymous and three non-synonymous, and a four base pair deletion resulting in a frame shift and early termination to produce a 743 amino acid putative protein. hGR DL-2 had a decrease in transactivation potential of more than 90%. Upon further analysis of the individual SNPs and deletion, one SNP, A829G, which results in a lysine to glutamic acid amino acid change at position 277, was found to increase the transactivation potential of hGR more than eight times the full-length reference. Furthermore, the hGRα-A829G isoform had a differential hyperactive response to various exogenous steroids. Increasing our knowledge as to how various SNPs affect hGR activity may help in understanding the unpredictable patient response to steroid treatment, and is a step towards personalizing patient care

Social and behavioural factors in Non-suspicious unexpected death in infancy; experience from metropolitan police project indigo investigation

BACKGROUND: Risk factors for Sudden Unexpected Death in Infancy (SUDI) are well described, and such cases are now investigated according to standard protocols. In London, Project Indigo of the Metropolitan Police provides a unique, detailed framework for such data collection. We investigate such data to provide a contemporary account of SUDI in a large city and further link data to publically available datasets to investigate interactions with social factors. METHODS: Retrospective analysis of data routinely collected by the Metropolitan Police Service in all cases of non-suspicious SUDI deaths in London during a six year period. RESULTS: SUDI deaths are associated with markers of social deprivation in London. A significant proportion of such deaths are associated with potentially modifiable risk factors such as cigarette smoking and co-sleeping, such behaviour also being associated with social factors, including accommodation issues. CONCLUSIONS: Routinely collected data provide valuable insight into patterns and associations of mortality, with SUDI remaining a significant issue in London. Risk factors include social disadvantage, which may manifest in part by affecting behavioural patterns such as co-sleeping and public health interventions to reduce rates require significant social modification