Semi-Parametric Seasonal Unit Root Tests

It is well known that (seasonal) unit root tests can be seriously affected by the presence of weak dependence in the driving shocks when this is not accounted for. In the non-seasonal case both parametric (based around augmentation of the test regression with lagged dependent variables) and semi-parametric (based around an estimator of the long run variance of the shocks) unit root tests have been proposed. Of these, the M class of unit root tests introduced by Stock (1999), Perron and Ng (1996) and Ng and Perron (2001), appear to be particularly successful, showing good finite sample size control even in the most problematic (near-cancellation) case where the shocks contain a strong negative moving average component. The aim of this paper is threefold. First we show the implications that neglected weak dependence in the shocks has on lag un-augmented versions of the well known regression based seasonal unit root tests of Hylleberg et al. (1990). Second, in order to complement extant parametrically augmented versions of the tests of Hylleberg et al. (1990), we develop semi-parametric seasonal unit root test procedures, generalising the methods developed in the non-seasonal case to our setting. Third, we compare the finite sample size and power properties of the parametric and semi-parametric seasonal unit root tests considered. Our results suggest that the superior size/power trade-off offered by the M approach in the non-seasonal case carries over to the seasonal case

A Bootstrap Stationarity Test for Predictive Regression Invalidity

We examine how the familiar spurious regression problem can manifest itself in the context of recently proposed predictability tests. For these tests to provide asymptotically valid inference, account has to be taken of the degree of persistence of the putative predictors. Failure to do so can lead to spurious over-rejections of the no predictability null hypothesis. A number of methods have been developed to achieve this. However, these approaches all make an underlying assumption that any predictability in the variable of interest is purely attributable to the predictors under test, rather than to any unobserved persistent latent variables, themselves uncorrelated with the predictors being tested. We show that where this assumption is violated, something that could very plausibly happen in practice, sizeable (spurious) rejections of the null can occur in cases where the variables under test are not valid predictors. In response, we propose a screening test for predictive regression invalidity based on a stationarity testing approach. In order to allow for an unknown degree of persistence in the putative predictors, and for both conditional and unconditional heteroskedasticity in the data, we implement our proposed test using a fixed regressor wild bootstrap procedure. We establish the asymptotic validity of this bootstrap test, which entails establishing a conditional invariance principle along with its bootstrap counterpart, both of which appear to be new to the literature and are likely to have important applications beyond the present context. We also show how our bootstrap test can be used, in conjunction with extant predictability tests, to deliver a two-step feasible procedure. Monte Carlo simulations suggest that our proposed bootstrap methods work well in finite samples. An illustration employing U.S. stock returns data demonstrates the practical usefulness of our procedures

Enterovesical Fistula: A Rare Complication of Urethral Catheterization

This report describes the case of an eighty-two-year old lady with an indwelling urethral catheter inserted eight years prior to her presentation to manage her urinary incontinence. She underwent radiotherapy for muscle-invasive bladder cancer (stage T2b) in 1991 and had a laparotomy and drainage of an appendicular abscess in her early twenties. She presented with a short history of fecaluria, pneumaturia, and passage of urine per rectum. On laparotomy she was found to have an inflated catheter balloon that has eroded through the bladder wall into the lumen of a terminal ileal segment. To our knowledge this is the first reported case in literature of a patient developing an enterovesical fistula as a result of a urethral catheter eroding through the bladder wall into the bowel lumen. There are numerous known complications of long-term urethral catheterization. They include recurrent urinary tract infections, recurrent pyelonephritis, sepsis, urethral stricture, blocked and retained catheters, among many other reported complications. This case describes an unusual presentation secondary to an even more unusual complication. This should be considered when handling patients with indwelling urethral catheters inserted in unhealthy bladders

Determining the Cointegration Rank in Heteroskedastic VAR Models of Unknown Order

We investigate the asymptotic and finite sample properties of a number of methods for estimating the cointegration rank in integrated vector autoregressive systems of unknown autoregressive order driven by heteroskedastic shocks. We allow for both conditional and unconditional heteroskedasticity of a very general form. We establish the conditions required on the penalty functions such that standard information criterion-based methods, such as the Bayesian information criterion [BIC], when employed either sequentially or jointly, can be used to consistently estimate both the cointegration rank and the autoregressive lag order. In doing so we also correct errors which appear in the proofs provided for the consistency of information-based estimators in the homoskedastic case by Aznar and Salvador (2002). We also extend the corpus of available large sample theory for the conventional sequential approach of Johansen (1995) and the associated wild bootstrap implementation thereof of Cavaliere, Rahbek and Taylor (2014) to the case where the lag order is unknown. In particular, we show that these methods remain valid under heteroskedasticity and an unknown lag length provided the lag length is first chosen by a consistent method, again such as the BIC. The relative finite sample properties of the different methods discussed are investigated in a Monte Carlo simulation study. The two best performing methods in this study are a wild bootstrap implementation of the Johansen (1995) procedure implemented with BIC selection of the lag length and joint IC approach (cf. Phillips, 1996) which uses the BIC to jointly select the lag order and the cointegration rank

Exploring metabolic consequences of CPS1 and CAD dysregulation in hepatocellular carcinoma by network reconstruction

Purpose: Hepatocellular carcinoma (HCC) is the fourth commonest cause of cancer-related mortality; it is associated with various genetic alterations, some involved in metabolic reprogramming. This study aimed to explore the potential metabolic impact of Carbamoyl Phosphate Synthase I (CPS1) and carbamoyl phosphate synthetase/aspartate transcarbamoylase/dihydroorotase (CAD) dysregulation through the reconstruction of a network that integrates information from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, Human Metabolome Database (HMDB) and Human Protein Atlas (HPA). Methods and Results: Existing literature was used to determine the roles of CPS1 and CAD in HCC. CPS1 downregulation is thought to play a role in hepatocarcinogenesis through an increased glutamine availability for de novo pyrimidine biosynthesis, which CAD catalyzes the first three steps for. KEGG, HMDB and HPA were used to reconstruct a network of relevant pathways, demonstrating the relationships between genes and metabolites using the MetaboSignal package in R. The network was filtered to exclude any duplicates, and those greater than three steps away from CPS1 or CAD. Consequently, a network of 18 metabolites, 28 metabolic genes and 1 signaling gene was obtained, which indicated expression profiles and prognostic information of each gene in the network. Conclusion: Information from different databases was collated to form an informative network that integrated different ‘-omics’ approaches, demonstrating the relationships between genetic and metabolic components of urea cycle and the de novo pyrimidine biosynthesis pathway. This study paves the way for further research by acting as a template to investigate the relationships between genes and metabolites, explore their potential roles in various diseases and aid the development of new screening and treatment methods through network reconstruction

Multi-effect distillation: a sustainable option to large-scale green hydrogen production using solar energy

Development of sustainable, gigawatt capacity green hydrogen will require both renewable energy and water inputs, along with careful management of the waste heat produced by these processes (i.e., 9.3e16.7 kWhth=kgH2 for a 70e80% stack efficiency, high heat value). Here we compare the water demands and operating costs for a solar-driven electrolyser facility (powered by solar PV) operating on desalinated seawater produced using reverse osmosis or low-temperature multi-effect distillation. The waste heat was managed via passive cooling, evaporative cooling or through thermal recovery. It was found that the costs for low-temperature multi-effect distillation were up to 85% lower than reverse osmosis and generated 50e270L/ kgH2 of surplus water for ancillary benefit. This work challenges conventional wisdom surrounding the use of membrane desalination for meeting the water demands, offering compelling reasons for thermal desalination to be employed in large-scale production of green hydrogen

Two Body Relaxation in Simulated Cosmological Haloes

This paper aims at quantifying discreetness effects, born of finite particle number, on the dynamics of dark matter haloes forming in the context of cosmological simulations. By generalising the standard calculation of two body relaxation to the case when the size and mass distribution are variable, and parametrising the time evolution using established empirical relations, we find that the dynamics of a million particle halo is noise-dominated within the inner percent of the final virial radius. Far larger particle numbers (~ 10^8) are required for the RMS perturbations to the velocity to drop to the 10 % level there. The radial scaling of the relaxation time is simple and strong: t_relax ~ r^2, implying that numbers >> 10^8 are required to faithfully model the very inner regions; artificial relaxation may thus constitute an important factor, contributing to the contradictory claims concerning the persistence of a power law density cusp to the very centre. The cores of substructure haloes can be many relaxation times old. Since relaxation first causes their expansion before recontraction occurs, it may render them either more difficult or easier to disrupt, depending on their orbital parameters. It may thus modify the characteristics of the subhalo distribution and effects of interactions with the parent. We derive simple closed form formulas for the characteristic relaxation times, as well as for the weak N-scaling reported by Diemand et al. when the main contribution comes from relaxing subhaloes (abridged).Comment: 11 Pages, 7 figs, Monthly Notices styl