Common Features in Vector Nonlinear Time Series Models

This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area. Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified. The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.

Professional and Non-Professional Written Travel Texts – Do They Have Common Features? : A Comparative Investigation on Travel Texts on Trysil, Norway

This study aims to investigate possible distinctions between professional and non-professional written travel texts all treating the same destination: the Norwegian ski resort Trysil. The study will investigate to what extent the different texts correlate with the genre of travel texts, as the travel texts are treated as personal narratives, and how they conform to a given structure for narratives and with guidelines for professional writers. Furthermore, the investigation aims to explore to what extent there are similarities and differences between the texts regarding the given structure. The texts will first be analysed and organized separately by macrorules and a news schema that are constructed specifically for these sorts of texts, in order to reveal their discourse structure, and then compared to each other. As the discourse structure of the different texts is revealed, it is seen that there are certain differences between the two different text types. Finally, seen that the text types differ in their structure, this study will show that despite the fact that journalists write stories, and that non-professional written stories are narratives, they do not share the same structure, and are constructed in different ways.

Estimating sectoral cycles using cointegration and common features

This paper investigates the degree of short run and long run co-movement in U.S. sectoral output data by estimating sectoraI trends and cycles. A theoretical model based on Long and Plosser (1983) is used to derive a reduced form for sectoral output from first principles. Cointegration and common features (cycles) tests are performed; sectoral output data seem to share a relatively high number of common trends and a relatively low number of common cycles. A special trend-cycle decomposition of the data set is performed and the results indicate a very similar cyclical behavior across sectors and a very different behavior for trends. Indeed. sectors cyclical components appear as one. In a variance decomposition analysis, prominent sectors such as Manufacturing and Wholesale/Retail Trade exhibit relatively important transitory shocks.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual horizons. The data to be used consists of metal-commodity prices in a monthly frequency from 1957 to 2012 from the International Financial Statistics of the IMF on individual metal series. We will also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009) , which are available for download. Regarding short- and long-run comovement, we will apply the techniques and the tests proposed in the common-feature literature to build parsimonious VARs, which possibly entail quasi-structural relationships between different commodity prices and/or between a given commodity price and its potential demand determinants. These parsimonious VARs will be later used as forecasting models to be combined to yield metal-commodity prices optimal forecasts. Regarding out-of-sample forecasts, we will use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates to forecast the returns and prices of metal commodities. With the forecasts of a large number of models (N large) and a large number of time periods (T large), we will apply the techniques put forth by the common-feature literature on forecast combinations. The main contribution of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding forecasting, we show that models incorporating (short-run) commoncycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation. Still, in most cases, forecast combination techniques outperform individual models.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual frequencies. Data consists of metal-commodity prices at a monthly and quarterly frequencies from 1957 to 2012, extracted from the IFS, and annual data, provided from 1900-2010 by the U.S. Geological Survey (USGS). We also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009). We investigate short- and long-run comovement by applying the techniques and the tests proposed in the common-feature literature. One of the main contributions of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding out-of-sample forecasts, our main contribution is to show the benefits of forecast-combination techniques, which outperform individual-model forecasts - including the random-walk model. We use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates and functional forms to forecast the returns and prices of metal commodities. Using a large number of models (N large) and a large number of time periods (T large), we apply the techniques put forth by the common-feature literature on forecast combinations. Empirically, we show that models incorporating (short-run) common-cycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation.

Residual-based Inference for Common Nonlinear Features

This paper investigates common nonlinear features in multivariate nonlinear autore-gressive models via testing the estimated residuals. A Wald-type test is proposed and itis asymptotically Chi-squared distributed. Simulation studies are given to examine thefinite-sample properties of the proposed test.

Constructing common-factor portfolios

In this paper we construct common-factor portfolios using a novel linear transformation of standard factor models extracted from large data sets of asset returns. The simple transformation proposed here keeps the basic properties of the usual factor transformations, although some new interesting properties are further attached to them. Some theoretical advantages are shown to be present. Also, their practical importance is confirmed in two applications: the performance of common-factor portfolios are shown to be superior to that of asset returns and factors commonly employed in the finance literature.

Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation

Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb(14F), and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hb promoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e. g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.

The impact of the subtropical South Atlantic SST on South American precipitation

The Community Climate Model (CCM3) from the National Center for Atmospheric Research (NCAR) is used to investigate the effect of the South Atlantic sea surface temperature (SST) anomalies on interannual to decadal variability of South American precipitation. Two ensembles composed of multidecadal simulations forced with monthly SST data from the Hadley Centre for the period 1949 to 2001 are analysed. A statistical treatment based on signal-to-noise ratio and Empirical Orthogonal Functions (EOF) is applied to the ensembles in order to reduce the internal variability among the integrations. The ensemble treatment shows a spatial and temporal dependence of reproducibility. High degree of reproducibility is found in the tropics while the extratropics is apparently less reproducible. Austral autumn (MAM) and spring (SON) precipitation appears to be more reproducible over the South America-South Atlantic region than the summer (DJF) and winter (JJA) rainfall. While the Inter-tropical Convergence Zone (ITCZ) region is dominated by external variance, the South Atlantic Convergence Zone (SACZ) over South America is predominantly determined by internal variance, which makes it a difficult phenomenon to predict. Alternatively, the SACZ over western South Atlantic appears to be more sensitive to the subtropical SST anomalies than over the continent. An attempt is made to separate the atmospheric response forced by the South Atlantic SST anomalies from that associated with the El Nino - Southern Oscillation (ENSO). Results show that both the South Atlantic and Pacific SSTs modulate the intensity and position of the SACZ during DJF. Particularly, the subtropical South Atlantic SSTs are more important than ENSO in determining the position of the SACZ over the southeast Brazilian coast during DJF. On the other hand, the ENSO signal seems to influence the intensity of the SACZ not only in DJF but especially its oceanic branch during MAM. Both local and remote influences, however, are confounded by the large internal variance in the region. During MAM and JJA, the South Atlantic SST anomalies affect the magnitude and the meridional displacement of the ITCZ. In JJA, the ENSO has relatively little influence on the interannual variability of the simulated rainfall. During SON, however, the ENSO seems to counteract the effect of the subtropical South Atlantic SST variations on convection over South America.

Gene and genotypic diversity of Phytophthora cinnamomi in South Africa and Australia revealed by DNA polymorphisms

Phytophthora cinnamomi isolates from South Africa and Australia were compared to assess genetic differentiation between the two populations. These two populations were analysed for levels of phenotypic diversity using random amplified polymorphic DNAs (RAPDs) and gene and genotypic diversity using restriction fragment length polymorphisms (RFLPs). Sixteen RAPD markers from four decanucleotide Operon primers and 34 RFLP alleles from 15 putative loci were used. A few isolates from Papua New Guinea known to posses alleles different from Australian isolates were also included for comparative purposes. South African and Australian P. cinnamomi populations were almost identical with an extremely low level of genetic distance between them (D-m = 0.003). Common features for the two populations include shared alleles, low levels of phenotypic/genotypic diversity, high clonality, and low observed and expected levels of heterozygosity. Furthermore, relatively high levels of genetic differentiation between mating type populations (D-m South Africa = 0.020 and D-m Australia = 0.025 respectively), negative fixation indices, and significant deviations from Hardy-Weinberg equilibrium, all provided evidence for the lack of frequent sexual reproduction in both populations. The data strongly suggest that both the South African and Australian P. cinnamomi populations are introduced.

Dietary salt restriction increases plasma lipoprotein and inflammatory marker concentrations in hypertensive patients

Background: Dietary salt restriction has been reported to adversely modify the plasma lipoprotein profile in hypertensive and in normotensive subjects. We investigated the effects of the low sodium intake (LSI) on the plasma lipoprotein profile and on inflammation and thrombosis biomarkers during the fasting and postprandial periods. Methods: Non-obese, non-treated hypertensive adults (n=41) were fed strictly controlled diets. An initial week on a control diet (CID, Na=160 mmol/day) was followed by 3 weeks on LSI (Na=60mmol/day). At admission and on the last day of each period, the 24-h ambulatory blood pressure was monitored and blood was drawn after an overnight fasting period and after a fat-rich test meal. Results: The dietary adherence was confirmed by 24-h urinary sodium excretion. Fasting triglyceride (TG), chylomicron-cholesterol, hsC-reactive protein (CRP), tumor necrosis factor-a (TNF-alpha). interleukin-6 (IL-6) concentrations, renin activity, aldosterone, insulin, and homeostasis model assessment insulin resistance (HOMA-IR) Values were higher, but non-esterified fatty acids (NEFA) were lower on LSI than on CD. For LSI, areas under the curve (AUC) of TG, chylomicron-cholesterol, apoB and the cholesterol/apoB ratio were increased, whereas AUC-NEFA was lowered. LSI did not modify body weight, hematocrit, fasting plasma cholesterol, glucose, adiponectin, leptin, fibrinogen and factor VII (FVII), and AUC of lipoprotein lipase and of lipoprotein remnants. Conclusion: LSI induced alterations in the plasma lipoproteins and in inflammatory markers that are common features of the metabolic syndrome. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

Syndromic and non-syndromic aneurysms of the human ascending aorta share activation of the Smad2 pathway

Common features such as elastic fibre destruction, mucoid accumulation, and smooth muscle cell apoptosis are co-localized in aneurysms of the ascending aorta of various aetiologies. Recent experimental studies reported an activation of TGF-beta in aneurysms related to Marfan (and Loeys-Dietz) syndrome. Here we investigate TGF-beta signalling in normal and pathological human ascending aortic wall in syndromic and non-syndromic aneurysmal disease. Aneurysmal ascending aortic specimens, classified according to aetiology: syndromic MFS (n = 15, including two mutations in TGFBR2), associated with BAV (n = 15) or degenerative forms (n = 19), were examined. We show that the amounts of TGF-beta 1 protein retained within and released by aneurysmal tissue were greater than for control aortic tissue, whatever the aetiology, contrasting with an unchanged TGF-beta 1 mRNA level. The increase in stored TGF-beta 1 was associated with enhanced LTBP-I protein and mRNA levels. These dysiregulations of the extracellular ligand are associated with higher phosphorylated Smad2 and Smad2 mRNA levels in the ascending aortic wall from all types of aneurysm. This activation correlated with the degree of elastic fibre fragmentation. Surprisingly, there was no consistent association between the nuclear location of pSmad2 and extracellular TGF-beta 1 and LTBP-I staining and between their respective mRNA expressions. In parallel, decorin. was focally increased in aneurysmal media, whereas biglycan was globally decreased in aneurysmal aortas. In conclusion, this study highlights independent dysregulations of TGF-beta retention and Smad2 signalling in syndromic and non-syndromic aneurysms of the ascending aorta. Copyright (C) 2009 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Immune responses in hookworm infections

Hookworms infect perhaps one-fifth of the entire human population, yet little is known about their interaction with our immune system. The two major species are Necator americanus, which is adapted to tropical conditions, and Ancylostoma duodenale, which predominates in more temperate zones. While having many common features, they also differ in several key aspects of their biology. Host immune responses are triggered by larval invasion of the skin, larval migration through the circulation and lungs, and worm establishment in the intestine, where adult worms feed on blood and mucosa while injecting various molecules that facilitate feeding and modulate host protective responses. Despite repeated exposure, protective immunity does not seem to develop in humans, so that infections occur in all age groups (depending on exposure patterns) and tend to be prolonged. Responses to both larval and adult worms have a characteristic T-helper type 2 profile, with activated mast cells in the gut mucosa, elevated levels of circulating immunoglobulin E, and eosinoophilia in the peripheral blood and local tissues, features also characteristic of type I hypersensitivity reactions. The longevity of adult hookworms is determined probably more by parasite genetics than by host immunity. However, many of the proteins released by the parasites seem to have immunomodulatory activity, presumably for self-protection. Advances in molecular biotechnology enable the identification and characterization of increasing numbers of these parasite molecules and should enhance our detailed understanding of the protective and pathogenetic mechanisms in hookworm infections.

Global distribution and genetic discontinuities of mangroves - emerging patterns in the evolution of Rhizophora

Mangroves are often described as a group of plants with common features and common origins based mostly on their broad distributional patterns, together with an erroneous view of comparable abilities in long-distance dispersal. However, whilst mangroves have common needs to adapt to rigorous environmental constraints associated with regular seawater inundation, individual taxa have developed different strategies and characteristics. Since mangroves are a genetically diverse group of mostly flowering plants, they may also have evolved at quite different geological periods, dispersed at different rates from different locations and developed different adaptive strategies. Current distributions of individual taxa show numerous instances of unusual extant distribution which demonstrate finite dispersal limitations, especially across open water. Our preliminary assessment of broad distribution and discontinuities reveals important patterns. Discontinuities, in the absence of current dispersal barriers, may be explained by persistent past barriers. As we learn more about discontinuities, we are beginning to appreciate their immense implications and what they might tell us about past geological conditions and how these might have influenced the distribution and evolution of mangroves. In this article, we describe emerging patterns in genetic relationships and distributions based on both current knowledge and preliminary results of our studies of molecular and morphometric characteristics of Rhizophora species in the Indo West Pacific region.