981 resultados para Panel Cointegration Test


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Purpose: To investigate the expression pattern of hypoxia-induced proteins identified as being involved in malignant progression of head-and-neck squamous cell carcinoma (HNSCC) and to determine their relationship to tumor pO 2 and prognosis. Methods and Materials: We performed immunohistochemical staining of hypoxia-induced proteins (carbonic anhydrase IX [CA IX], BNIP3L, connective tissue growth factor, osteopontin, ephrin A1, hypoxia inducible gene-2, dihydrofolate reductase, galectin-1, IκB kinase β, and lysyl oxidase) on tumor tissue arrays of 101 HNSCC patients with pretreatment pO 2 measurements. Analysis of variance and Fisher's exact tests were used to evaluate the relationship between marker expression, tumor pO 2, and CA IX staining. Cox proportional hazard model and log-rank tests were used to determine the relationship between markers and prognosis. Results: Osteopontin expression correlated with tumor pO 2 (Eppendorf measurements) (p = 0.04). However, there was a strong correlation between lysyl oxidase, ephrin A1, and galectin-1 and CA IX staining. These markers also predicted for cancer-specific survival and overall survival on univariate analysis. A hypoxia score of 0-5 was assigned to each patient, on the basis of the presence of strong staining for these markers, whereby a higher score signifies increased marker expression. On multivariate analysis, increasing hypoxia score was an independent prognostic factor for cancer-specific survival (p = 0.015) and was borderline significant for overall survival (p = 0.057) when adjusted for other independent predictors of outcomes (hemoglobin and age). Conclusions: We identified a panel of hypoxia-related tissue markers that correlates with treatment outcomes in HNSCC. Validation of these markers will be needed to determine their utility in identifying patients for hypoxia-targeted therapy. © 2007 Elsevier Inc. All rights reserved.

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Design Pressure Test 2013 was a full-day intensive design immersion creative event run on Saturday 3 August 2013, at the QUT Faculty of Creative Industries J Block Design Lab Workshop in Brisbane, Australia, for 25 self-selected high-achieving junior and middle school (year 5-9) students, as part of the Queensland Academies ‘Young Scholars’ Program. Facilitated by tertiary interior design, fashion design and industrial design educators, technicians and six tertiary interior design and fashion design students, the workshop explored design process, environmental impact, the material properties and structural integrity of cardboard, construction techniques, and the production and evaluation of furniture design prototypes. This action research study aimed to facilitate an awareness in young people, of the role and scope of design within our society, the environmental ramifications of design decisions, and the value of design thinking skills in generating strategies to solve basic to complex challenges. It also aimed to investigate the value of collaboration between junior and middle school students, tertiary design educators and students and industry professionals in design awareness, and inspiring post-secondary pathways and idea generation for education. During the creative event, students utilised mathematics skills and developed sketching, making, communication, presentation and collaboration skills to improve their design process, while considering social, cultural and environmental opportunities. Through a series of hands-on collaborative design experiments, participants explored in teams of five, the opportunities available using cardboard as a material – inspiring both functional and aesthetic design solutions. Underpinned by the State Library of Queensland Design Minds Website ‘inquire, ideate and implement’ model of design thinking, the experiments culminated in the development of a detailed client brief, the design and fabrication of a furniture item for seating, and then a team presentation of prototypes to a panel of judges from the professions of architecture, interior design and industrial design, viewed also by parents. The final test for structural integrity was measured by the hoisting down of an adult body weight onto the fabricated seat. The workshop was filmed for the television program ‘Totally Wild’ for dissemination nationally (over 200,000 viewing audience) of the value of design and the Design Minds model to a wider target youth audience.

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In June 2012 Prime Minister Gillard appointed an Expert Panel on Asylum Seekers to provide advice on policy options 'to prevent asylum seekers rising their lives on dangerous boat journeys to Australia'. This article examines the establishment of that Committee against the backdrop of an increasing number of boat arrivals, of deaths at sea and the failure of Government policy responses to prevent them. It examines the recommendations of the Expert Panel and considers the punitive outcome of some of these recommendations including the 'no advantage' test. It evaluates Kevin Rudd's Regional Resettlement Arrangement with Papua New Guinea and concludes that Australian and regional initiatives need to focus on protection of asylum seekers, not deterrence or avoidance of international obligations

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Non-parametric difference tests such as triangle and duo-trio tests traditionally are used to establish differences or similarities between products. However they only supply the researcher with partial answers and often further testing is required to establish the nature, size and direction of differences. This paper looks at the advantages of the difference from control (DFC) test (also known as degree of difference test) and discusses appropriate applications of the test. The scope and principle of the test, panel composition and analysis of results are presented with the aid of suitable examples. Two of the major uses of the DFC test are in quality control and shelf-life testing. The role DFC takes in these areas and the use of other tests to complement the testing is discussed. Controls or standards are important in both these areas and the use of standard products, mental and written standards and blind controls are highlighted. The DFC test has applications in products where the duo-trio and triangle tests cannot be used because of the normal heterogeneity of the product. While the DFC test is a simple difference test it can be structured to give the researcher more valuable data and scope to make informed decisions about their product.

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In the thesis we consider inference for cointegration in vector autoregressive (VAR) models. The thesis consists of an introduction and four papers. The first paper proposes a new test for cointegration in VAR models that is directly based on the eigenvalues of the least squares (LS) estimate of the autoregressive matrix. In the second paper we compare a small sample correction for the likelihood ratio (LR) test of cointegrating rank and the bootstrap. The simulation experiments show that the bootstrap works very well in practice and dominates the correction factor. The tests are applied to international stock prices data, and the .nite sample performance of the tests are investigated by simulating the data. The third paper studies the demand for money in Sweden 1970—2000 using the I(2) model. In the fourth paper we re-examine the evidence of cointegration between international stock prices. The paper shows that some of the previous empirical results can be explained by the small-sample bias and size distortion of Johansen’s LR tests for cointegration. In all papers we work with two data sets. The first data set is a Swedish money demand data set with observations on the money stock, the consumer price index, gross domestic product (GDP), the short-term interest rate and the long-term interest rate. The data are quarterly and the sample period is 1970(1)—2000(1). The second data set consists of month-end stock market index observations for Finland, France, Germany, Sweden, the United Kingdom and the United States from 1980(1) to 1997(2). Both data sets are typical of the sample sizes encountered in economic data, and the applications illustrate the usefulness of the models and tests discussed in the thesis.

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The likelihood ratio test of cointegration rank is the most widely used test for cointegration. Many studies have shown that its finite sample distribution is not well approximated by the limiting distribution. The article introduces and evaluates by Monte Carlo simulation experiments bootstrap and fast double bootstrap (FDB) algorithms for the likelihood ratio test. It finds that the performance of the bootstrap test is very good. The more sophisticated FDB produces a further improvement in cases where the performance of the asymptotic test is very unsatisfactory and the ordinary bootstrap does not work as well as it might. Furthermore, the Monte Carlo simulations provide a number of guidelines on when the bootstrap and FDB tests can be expected to work well. Finally, the tests are applied to US interest rates and international stock prices series. It is found that the asymptotic test tends to overestimate the cointegration rank, while the bootstrap and FDB tests choose the correct cointegration rank.

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Bootstrap likelihood ratio tests of cointegration rank are commonly used because they tend to have rejection probabilities that are closer to the nominal level than the rejection probabilities of the correspond- ing asymptotic tests. The e¤ect of bootstrapping the test on its power is largely unknown. We show that a new computationally inexpensive procedure can be applied to the estimation of the power function of the bootstrap test of cointegration rank. The bootstrap test is found to have a power function close to that of the level-adjusted asymp- totic test. The bootstrap test estimates the level-adjusted power of the asymptotic test highly accurately. The bootstrap test may have low power to reject the null hypothesis of cointegration rank zero, or underestimate the cointegration rank. An empirical application to Euribor interest rates is provided as an illustration of the findings.

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Many economic events involve initial observations that substantially deviate from long-run steady state. Initial conditions of this type have been found to impact diversely on the power of univariate unit root tests, whereas the impact on multivariate tests is largely unknown. This paper investigates the impact of the initial condition on tests for cointegration rank. We compare the local power of the widely used likelihood ratio (LR) test with the local power of a test based on the eigenvalues of the companion matrix. We find that the power of the LR test is increasing in the magnitude of the initial condition, whereas the power of the other test is decreasing. The behaviour of the tests is investigated in an application to price convergence.

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Solar photovoltaic power plants are ideally located in regions with high insolation levels. Photovoltaic performance is affected by high cell temperatures, soiling, mismatch and other balance-of-systems related losses. It is crucial to understand the significance of each of these losses on system performance. Soiling, highly dependent on installation conditions, is a complex performance issue to accurately quantify. The settlement of dust on panel surfaces may or may not be uniform depending on local terrain and environmental factors such as ambient temperature, wind and rainfall. It is essential to investigate the influence of dust settlement on the operating characteristics of photovoltaic systems to better understand losses in performance attributable to soiling. The current voltage (I-V) characteristics of photovoltaic panels reveal extensive information to support degradation analysis of the panels. This paper attempts to understand performance losses due to dust through a dynamic study into the I-V characteristics of panels under varying soiling conditions in an outdoor experimental test-bed. Further, the results of an indoor study simulating the performance of photovoltaic panels under different dust deposition regimes are discussed in this paper. (C) 2014 Monto Mani. Published by Elsevier Ltd. This is all open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

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In a recent paper Leong-Huang:2010 {Journal of Applied Statistics 37, 215–233} proposed a wavelet-correlation-based approach to test for cointegration between two time series. However, correlation and cointegration are two different concepts even when wavelet analysis is used. It is known that statistics based on nonstationary integrated variables have non-standard asymptotic distributions. However, wavelet analysis offsets the integrating order of nonstationary series so that traditional asymptotics on stationary variables suffices to ascertain the statistical properties of wavelet-based statistics. Based on this, this note shows that wavelet correlations cannot be used as a test of cointegration.

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The analysis of the evolution of the M3 money aggregate is an important element in the definition and implementation of monetary policy for the ECB. A well-defined and stable long run demand function is an essential requisite for M3 to be a valid monetary tool. Therefore, this paper analyzes based in cointegration techniques the existence of a long run money demand, estimating it and testing its stability for the Euro Area and for ten of its member countries. Specifically, bearing in mind the high degree of monetary instability that the current economic crisis has created in the Euro Area, we also test whether this has had a noticeable impact in the cointegration among real money demand and its determinants. The analysis gives evidence of the existence of a long run relationship when the aggregated Euro Area and six of the ten countries are considered. However, these relationships are highly instable since the outbreak of the financial crisis, leading in some cases to even rejecting cointegration. All this suggests that the ECB’s strategy of focusing in the M3 monetary aggregates could not be a convenient approach under the current circumstances

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A design and optimization procedure developed and used for a propeller installed on a twin-semitunnel-hull ship navigating in very shallow and icy water under heavy load conditions is presented. The base propeller for this vessel was first determined using classic design routines under open-water condition with existing model test data. In the optimization process, a panel method code (PROPELLA) was used to vary the pitch values and distributions and take into account the inflow wake distribution, tunnel gap, and cavitation effects. The optimized propeller was able to improve a ship speed of 0.02 knots higher than the desired speed and 0.06 knots higher than the classic B-series propeller. The analysis of the effect of inflow wake, hull tunnel, cavitation, and blade rake angle on propulsive performance is the focus of this paper.

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This paper investigates the performance of the tests proposed by Hadri and by Hadri and Larsson for testing for stationarity in heterogeneous panel data under model misspecification. The panel tests are based on the well known KPSS test (cf. Kwiatkowski et al.) which considers two models: stationarity around a deterministic level and stationarity around a deterministic trend. There is no study, as far as we know, on the statistical properties of the test when the wrong model is used. We also consider the case of the simultaneous presence of the two types of models in a panel. We employ two asymptotics: joint asymptotic, T, N -> infinity simultaneously, and T fixed and N allowed to grow indefinitely. We use Monte Carlo experiments to investigate the effects of misspecification in sample sizes usually used in practice. The results indicate that the assumption that T is fixed rather than asymptotic leads to tests that have less size distortions, particularly for relatively small T with large N panels (micro-panels) than the tests derived under the joint asymptotics. We also find that choosing a deterministic trend when a deterministic level is true does not significantly affect the properties of the test. But, choosing a deterministic level when a deterministic trend is true leads to extreme over-rejections. Therefore, when unsure about which model has generated the data, it is suggested to use the model with a trend. We also propose a new statistic for testing for stationarity in mixed panel data where the mixture is known. The performance of this new test is very good for both cases of T asymptotic and T fixed. The statistic for T asymptotic is slightly undersized when T is very small (

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Invited panel speaker at a Jean Monnet Chair funded research workshop organised by the Europa Institute, School of Law, University of Edinburgh (9 December 2011), http://www.pol.ed.ac.uk/research_themes/index/jean_monnet_centre_of_excellence/principles_of_market_access_workshop

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In this paper, we test the Prebish-Singer (PS) hypothesis, which states that real commodity prices decline in the long run, using two recent powerful panel data stationarity tests accounting for cross-sectional dependence and a structural break. We find that the hypothesis cannot be rejected for most commodities other than oil.