Forecasting unstable processes

Previous analysis on forecasting theory either assume knowing the true parameters or assume the stationarity of the series. Not much are known on the forecasting theory for nonstationary process with estimated parameters. This paper investigates the recursive least square forecast for stationary and nonstationary processes with unit roots. We first prove that the accumulated forecast mean square error can be decomposed into two components, one of which arises from estimation uncertainty and the other from the disturbance term. The former, of the order of $\log(T)$, is of second order importance to the latter term, of the order T. However, since the latter is common for all predictors, it is the former that determines the property of each predictor. Our theorem implies that the improvement of forecasting precision is of the order of $\log(T)$ when existence of unit root is properly detected and taken into account. Also, our theorem leads to a new proof of strong consistency of predictive least squares in model selection and a new test of unit root where no regression is needed. The simulation results confirm our theoretical findings. In addition, we find that while mis-specification of AR order and under-specification of the number of unit root have marginal impact on forecasting precision, over-specification of the number of unit root strongly deteriorates the quality of long term forecast. As for the empirical study using Taiwanese data, the results are mixed. Adaptive forecast and imposing unit root improve forecast precision for some cases but deteriorate forecasting precision for other cases.Comment: Published at http://dx.doi.org/10.1214/074921706000000969 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Identifying the Predictors for Financial Crisis Using Gibbs Sampler

The Asian financial crisis broke out in Thailand in July 1997, and rapidly spread throughout the neighboring countries. An important question then arises? Is it possible to predict next financial crisis? If yes, then what are the predictors? The answer lies in combined usage of economic theory and econometric methods. By using the economic theory, one can locate possible potential crisis predictors whereas appropriate econometric models can pinpoint effective ones. In this paper we suggest using the Stochastic Search Variable Selection (SSVS) developed by George and McCulloch (1993) to identify the crisis predictors. As is suggested by the name, SSVS stochastically searches for practically significant variables. Each variable coefficient is assumed to come from a mixture of two normal variates with respectively large and small variances. For the former case, this variable is considered as insignificant and should be excluded from the model whereas for the latter, this variable is significant and should be included in the model. SSVS is not affected by the ordering of the candidate variables and is particularly effective when the sample size is much smaller than the number of all possible models. By employing SSVS method, we conclude that annual growth rate of money supply, $M_2$, and the ratio of government debt to GDP are promising predictors for financial crisis. It is worth mentioning that the frequently mentioned factors, such as ratio of total foreign reserve to GDP and the ratio of current deficit to GDP are not selected by our analysis. Our empirical analysis implies that monetary and fiscal policy play a crucial role in exploring the Asian financial crisis.early warning

Identifying the Predictors for Financial Crisis Using Gibbs Sampler

The Asian financial crisis broke out in Thailand in July 1997, and rapidly spread throughout the neighboring countries. An important question then arises? Is it possible to predict next financial crisis? If yes, then what are the predictors? The answer lies in combined usage of economic theory and econometric methods. By using the economic theory, one can locate possible potential crisis predictors whereas appropriate econometric models can pinpoint effective ones. In this paper we suggest using the Stochastic Search Variable Selection (SSVS) developed by George and McCulloch (1993) to identify the crisis predictors. As is suggested by the name, SSVS stochastically searches for practically significant variables. Each variable coefficient is assumed to come from a mixture of two normal variates with respectively large and small variances. For the former case, this variable is considered as insignificant and should be excluded from the model whereas for the latter, this variable is significant and should be included in the model. SSVS is not affected by the ordering of the candidate variables and is particularly effective when the sample size is much smaller than the number of all possible models. By employing SSVS method, we conclude that annual growth rate of money supply, $M_2$, and the ratio of government debt to GDP are promising predictors for financial crisis. It is worth mentioning that the frequently mentioned factors, such as ratio of total foreign reserve to GDP and the ratio of current deficit to GDP are not selected by our analysis. Our empirical analysis implies that monetary and fiscal policy play a crucial role in exploring the Asian financial crisis.Financial crisis, early warning

Modeling lunar calendar effects in taiwan

The three most important Chinese holidays, Chinese New Year, the Dragon- boat Festival, and Mid-Autumn Holiday have dates determined by a lunar calendar and move between two solar months. Consumption, production, and other economic behavior in countries with large Chinese population including Taiwan are strongly affected by these holidays. For example, production accelerates before lunar new year, almost completely stops during the holidays and gradually rises to an average level after the holidays. This moving holiday often creates difficulty for empirical modeling using monthly data and this paper employs an approach that uses regressors for each holiday to distinguish effects before, during and after holiday. Assuming that the holiday effect is the same for each day of the interval over which the regressor is nonzero in a given year, the value of the regressor in a given month is the proportion of this interval that falls in the month. Bell and Hillmer (1983) proposed such a regressor for Easter which is now extensively used in the U.S. and Europe. We apply the Bell and Hillmer's method to analyze ten important series in Taiwan, which might be affected by moving holidays. AICC and out-of-sample forecast performance were used for selecting number of holiday regressors and their interval lengths. The results are further checked by various diagnostic checking statistics including outlier detection and sliding spans analysis. The empirical results support this approach. Adding holiday regressors can effectively control the impact of moving holidays and improves the seasonal decomposition. AICC and accumulated forecast error are useful in regressor selection. We find that unemployment rates in Taiwan have holiday effects and seasonal factors cannot be consistently estimated unless the holiday factor is included. Furthermore, as the unemployment is rising, the magnitude of holiday and seasonal factor are decreasing. Finally, we find that holiday factors are generally smaller than seasonal factors but should not be ignored.lunar new year, moving holiday, seasonal adjustment, X12-ARIMA

Toward optimal multistep forecasts in non-stationary autoregressions

This paper investigates multistep prediction errors for non-stationary autoregressive processes with both model order and true parameters unknown. We give asymptotic expressions for the multistep mean squared prediction errors and accumulated prediction errors of two important methods, plug-in and direct prediction. These expressions not only characterize how the prediction errors are influenced by the model orders, prediction methods, values of parameters and unit roots, but also inspire us to construct some new predictor selection criteria that can ultimately choose the best combination of the model order and prediction method with probability 1. Finally, simulation analysis confirms the satisfactory finite sample performance of the newly proposed criteria.Comment: Published in at http://dx.doi.org/10.3150/08-BEJ165 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

Synergistic effect of imp/ostA and msbA in hydrophobic drug resistance of Helicobacter pylori

<p>Abstract</p> <p>Background</p> <p>Contamination of endoscopy equipment by <it>Helicobacter pylori </it>(<it>H. pylori</it>) frequently occurs after endoscopic examination of <it>H. pylori</it>-infected patients. In the hospital, manual pre-cleaning and soaking in glutaraldehyde is an important process to disinfect endoscopes. However, this might not be sufficient to remove <it>H. pylori </it>completely, and some glutaraldehyde-resistant bacteria might survive and be passed to the next patient undergoing endoscopic examination through unidentified mechanisms. We identified an Imp/OstA protein associated with glutaraldehyde resistance in a clinical strain, NTUH-C1, from our previous study. To better understand and manage the problem of glutaraldehyde resistance, we further investigated its mechanism.</p> <p>Results</p> <p>The minimal inhibitory concentrations (MICs) of glutaraldehyde andexpression of <it>imp/ostA </it>RNA in 11 clinical isolates from the National Taiwan University Hospital were determined. After glutaraldehyde treatment, RNA expression in the strains with the MICs of 4–10 μg/ml was higher than that in strains with the MICs of 1–3 μg/ml. We examined the full-genome expression of strain NTUH-S1 after glutaraldehyde treatment using a microarray and found that 40 genes were upregulated and 31 genes were downregulated. Among the upregulated genes, <it>imp/ostA </it>and <it>msbA</it>, two putative lipopolysaccharide biogenesis genes, were selected for further characterization. The sensitivity to glutaraldehyde or hydrophobic drugs increased in both of <it>imp/ostA </it>and <it>msbA </it>single mutants. The <it>imp/ostA </it>and <it>msbA </it>double mutant was also hypersensitive to these chemicals. The lipopolysaccharide contents decreased in individual <it>imp/ostA </it>and <it>msbA </it>mutants and dramatically reduced in the <it>imp/ostA </it>and <it>msbA </it>double mutant. Outer membrane permeability assay demonstrated that the <it>imp/ostA </it>and <it>msbA </it>double mutation resulted in the increase of outer membrane permeability. Ethidium bromide accumulation assay demonstrated that MsbA was involved in efflux of hydrophobic drugs.</p> <p>Conclusion</p> <p>The expression levels of <it>imp/ostA </it>and <it>msbA </it>were correlated with glutaraldehyde resistance in clinical isolates after glutaraldehyde treatment. Imp/OstA and MsbA play a synergistic role in hydrophobic drugs resistance and lipopolysaccharide biogenesis in <it>H. pylori</it>.</p

Caffeic acid phenethyl amide ameliorates ischemia/reperfusion injury and cardiac dysfunction in streptozotocin-induced diabetic rats

BACKGROUND: Caffeic acid phenethyl ester (CAPE) has been shown to protect the heart against ischemia/reperfusion (I/R) injury by various mechanisms including its antioxidant effect. In this study, we evaluated the protective effects of a CAPE analog with more structural stability in plasma, caffeic acid phenethyl amide (CAPA), on I/R injury in streptozotocin (STZ)-induced type 1 diabetic rats. METHODS: Type 1 diabetes mellitus was induced in Sprague–Dawley rats by a single intravenous injection of 60 mg/kg STZ. To produce the I/R injury, the left anterior descending coronary artery was occluded for 45 minutes, followed by 2 hours of reperfusion. CAPA was pretreated intraperitoneally 30 minutes before reperfusion. An analog devoid of the antioxidant property of CAPA, dimethoxyl CAPA (dmCAPA), and a nitric oxide synthase (NOS) inhibitor (Nω-nitro-l-arginine methyl ester [l-NAME]) were used to evaluate the mechanism involved in the reduction of the infarct size following CAPA-treatment. Finally, the cardioprotective effect of chronic treatment of CAPA was analyzed in diabetic rats. RESULTS: Compared to the control group, CAPA administration (3 and 15 mg/kg) significantly reduced the myocardial infarct size after I/R, while dmCAPA (15 mg/kg) had no cardioprotective effect. Interestingly, pretreatment with a NOS inhibitor, (l-NAME, 3 mg/kg) eliminated the effect of CAPA on myocardial infarction. Additionally, a 4-week CAPA treatment (1 mg/kg, orally, once daily) started 4 weeks after STZ-induction could effectively decrease the infarct size and ameliorate the cardiac dysfunction by pressure-volume loop analysis in STZ-induced diabetic animals. CONCLUSIONS: CAPA, which is structurally similar to CAPE, exerts cardioprotective activity in I/R injury through its antioxidant property and by preserving nitric oxide levels. On the other hand, chronic CAPA treatment could also ameliorate cardiac dysfunction in diabetic animals

Prophage Excision in Streptococcus pneumoniae Serotype 19A ST320 Promote Colonization: Insight Into Its Evolution From the Ancestral Clone Taiwan 19F-14 (ST236)

Streptococcus pneumoniae 19A ST320, a multidrug-resistant strain with high disease severity that notoriously spread before the use of expanded pneumococcal conjugate vaccines, was derived from a capsular switching event between an international strain Taiwan 19F-14 (ST236) and a serotype 19A strain. However, the molecular mechanisms underlying the adaptive evolution of 19F ST236 to 19A ST320 are unknown. In this study, we compared 19A ST320 to its ancestral clone, 19F ST236, in terms of adherence to respiratory epithelial cells, whole transcriptome, and ability to colonize a young mouse model. Serotype 19A ST320 showed five-fold higher adherence to A549 cells than serotype 19F ST236. High-throughput mRNA sequencing identified a prophage region located between dnaN and ychF in both strains; however, the genes in this region were expressed at significantly higher levels in 19A ST320 than in 19F ST236. Analysis by polymerase chain reaction (PCR) showed that the prophage is able to spontaneously excise from the chromosome and form a circular episome in 19A ST320, but not in 19F ST236. Deletion of the integrase in the prophage of 19A ST320 decreased spontaneous excision and cell adherence, which were restored by complementation. Competition experiments in mice showed that the integrase mutant was six-fold less competitive than the 19A ST320 parent (competitive index [CI]: 0.16; p = 0.02). The 19A ST320 prophage-deleted strain did not change cell adherence capacity, whereas prophage integration strains (integrase mutant and 19F) had decreased expression of the down-stream ychF gene compared to that of 19A ST320. Further deletion of ychF significantly reduced cell adherence. In conclusions, these findings suggest that spontaneous prophage induction confers a competitive advantage to virulent pneumococci