Single nucleotide polymorphisms predisposing to asthma in children of Mauritian Indian and Chinese Han ethnicity

Our objective was to investigate the distributions of six single nucleotide polymorphisms (SNPs) MS4A2 E237G, MS4A2 C-109T, ADRB2 R16G, IL4RA I75V,IL4 C-590T, and IL13 C1923T in Mauritian Indian and Chinese Han children with asthma. This case-control association study enrolled 382 unrelated Mauritian Indian children, 193 with asthma and 189 healthy controls, and 384 unrelated Chinese Han children, 192 with asthma and 192 healthy controls. The SNP loci were genotyped using polymerase chain reaction (PCR)-restriction fragment length polymorphism for the Chinese Han samples and TaqMan real-time quantitative PCR for the Mauritian Indian samples. In the Mauritian Indian children, there was a significant difference in the distribution of IL13 C1923T between the asthma and control groups (P=0.033). The frequency of IL13 C1923T T/T in the Mauritian Indian asthma group was significantly higher than in the control group [odds ratio (OR)=2.119, 95% confidence interval=1.048-4.285]. The Chinese Han children with asthma had significantly higher frequencies ofMS4A2 C-109T T/T (OR=1.961, P=0.001) and ADRB2 R16G A/A (OR=2.575, P=0.000) than the control group. The IL13 C1923T locus predisposed to asthma in Mauritian Indian children, which represents an ethnic difference from the Chinese Han population. TheMS4A2 C-109T T/T and ADRB2 R16G A/Agenotypes were associated with asthma in the Chinese Han children.

Associations between CD36 gene polymorphisms and susceptibility to coronary artery heart disease

Associations between polymorphisms of the CD36 gene and susceptibility to coronary artery heart disease (CHD) are not clear. We assessed allele frequencies and genotype distributions of CD36 gene polymorphisms in 112 CHD patients and 129 control patients using semi-quantitative polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) analysis. Additionally, we detected CD36 mRNA expression by real-time quantitative PCR, and we quantified plasma levels of oxidized low-density lipoprotein (ox-LDL) using an enzyme-linked immunosorbent assay (ELISA). There were no significant differences between the two groups (P>0.05) in allele frequencies of rs1761667 or in genotype distribution and allele frequencies of rs3173798. The genotype distribution of rs1761667 significantly differed between CHD patients and controls (P=0.034), with a significantly higher frequency of the AG genotype in the CHD group compared to the control group (P=0.011). The plasma levels of ox-LDL in patients with the AG genotype were remarkably higher than those with the GG and AA genotypes (P=0.010). In a randomized sample taken from patients in the two groups, the CD36 mRNA expression of the CHD patients was higher than that of the controls. In CHD patients, the CD36 mRNA expression in AG genotype patients was remarkably higher than in those with an AA genotype (P=0.005). After adjusted logistic regression analysis, the AG genotype of rs1761667 was associated with an increased risk of CHD (OR=2.337, 95% CI=1.336-4.087, P=0.003). In conclusion, the rs1761667 polymorphism may be closely associated with developing CHD in the Chongqing Han population of China, and an AG genotype may be a genetic susceptibility factor for CHD.

Extracting Ramachandran torsional angle distributions from 2D NMR data using Tikhonov regularization /

Solid state nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for studying structural and dynamical properties of disordered and partially ordered materials, such as glasses, polymers, liquid crystals, and biological materials. In particular, twodimensional( 2D) NMR methods such as ^^C-^^C correlation spectroscopy under the magicangle- spinning (MAS) conditions have been used to measure structural constraints on the secondary structure of proteins and polypeptides. Amyloid fibrils implicated in a broad class of diseases such as Alzheimer's are known to contain a particular repeating structural motif, called a /5-sheet. However, the details of such structures are poorly understood, primarily because the structural constraints extracted from the 2D NMR data in the form of the so-called Ramachandran (backbone torsion) angle distributions, g{^,'4)), are strongly model-dependent. Inverse theory methods are used to extract Ramachandran angle distributions from a set of 2D MAS and constant-time double-quantum-filtered dipolar recoupling (CTDQFD) data. This is a vastly underdetermined problem, and the stability of the inverse mapping is problematic. Tikhonov regularization is a well-known method of improving the stability of the inverse; in this work it is extended to use a new regularization functional based on the Laplacian rather than on the norm of the function itself. In this way, one makes use of the inherently two-dimensional nature of the underlying Ramachandran maps. In addition, a modification of the existing numerical procedure is performed, as appropriate for an underdetermined inverse problem. Stability of the algorithm with respect to the signal-to-noise (S/N) ratio is examined using a simulated data set. The results show excellent convergence to the true angle distribution function g{(j),ii) for the S/N ratio above 100.

Market reactions to changes in the Nasdaq-100 Index membership

We examine stock market reactions around the Nasdaq-100 Index reconstitutions. We find a symmetric and transitory price response accompanied by a significant increase in trading volume on the effective date. Firms added to the Nasdaq-100 Index experience significant increases in institutional ownership, the number of market makers, and the number of shareholders. In contrast, firms removed from the index show significant decreases in the number of institutional shareholders. Additions to the Nasdaq-100 Index also show significant increases in four liquidity measures, whereas deletions demonstrate significant decreases in two liquidity measures. These changes in liquidity are related to the abnormal return on the announcement day. Taken together, the results suggest support for the price pressure, liquidity, and investor awareness hypotheses.

Letter to the Estate of W.D. Woodruff from S. Mitchell, secretary of the Lincoln Paper Mills Company

Letter to the Estate of W.D. Woodruff from S. Mitchell, secretary of the Lincoln Paper Mills Company (1 page, printed). This is a notice of the 43rd annual meeting of the shareholders of the Lincoln Paper Mills Company, Limited. This is accompanied by an envelope, Feb. 7, 1921.

Letter to Mrs. A.L. Woodruff from S. Mitchell, secretary of the Lincoln Paper Mills Company

Letter to Mrs. A.L. Woodruff from S. Mitchell, secretary of the Lincoln Paper Mills Company (1 page, printed). This is a notice of the 43rd annual meeting of the shareholders of the Lincoln Paper Mills Company, Limited. This is accompanied by an envelope, Feb. 7, 1921.

Letter to Dr. T.A. Woodruff from S. Mitchell, secretary of the Lincoln Paper Mills Company

Letter to Dr. T.A. Woodruff from S. Mitchell, secretary of the Lincoln Paper Mills Company (1 page, printed). This is a notice of the 43rd annual meeting of the shareholders of the Lincoln Paper Mills Company, Limited. This is accompanied by an envelope, Feb. 7, 1921.

Exact Nonparametric Two-Sample Homogeneity Tests for Possibly Discrete Distributions.

In this paper, we study several tests for the equality of two unknown distributions. Two are based on empirical distribution functions, three others on nonparametric probability density estimates, and the last ones on differences between sample moments. We suggest controlling the size of such tests (under nonparametric assumptions) by using permutational versions of the tests jointly with the method of Monte Carlo tests properly adjusted to deal with discrete distributions. We also propose a combined test procedure, whose level is again perfectly controlled through the Monte Carlo test technique and has better power properties than the individual tests that are combined. Finally, in a simulation experiment, we show that the technique suggested provides perfect control of test size and that the new tests proposed can yield sizeable power improvements.

Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models

In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR) with applications to asset pricing models. We focus on departures from the assumption of i.i.d. errors assumption, at univariate and multivariate levels, with Gaussian and non-Gaussian (including Student t) errors. The univariate tests studied extend existing exact procedures by allowing for unspecified parameters in the error distributions (e.g., the degrees of freedom in the case of the Student t distribution). The multivariate tests are based on properly standardized multivariate residuals to ensure invariance to MLR coefficients and error covariances. We consider tests for serial correlation, tests for multivariate GARCH and sign-type tests against general dependencies and asymmetries. The procedures proposed provide exact versions of those applied in Shanken (1990) which consist in combining univariate specification tests. Specifically, we combine tests across equations using the MC test procedure to avoid Bonferroni-type bounds. Since non-Gaussian based tests are not pivotal, we apply the “maximized MC” (MMC) test method [Dufour (2002)], where the MC p-value for the tested hypothesis (which depends on nuisance parameters) is maximized (with respect to these nuisance parameters) to control the test’s significance level. The tests proposed are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995. Our empirical results reveal the following. Whereas univariate exact tests indicate significant serial correlation, asymmetries and GARCH in some equations, such effects are much less prevalent once error cross-equation covariances are accounted for. In addition, significant departures from the i.i.d. hypothesis are less evident once we allow for non-Gaussian errors.

Methods to Estimate Dynamic Stochastic General Equilibrium Models

This paper employs the one-sector Real Business Cycle model as a testing ground for four different procedures to estimate Dynamic Stochastic General Equilibrium (DSGE) models. The procedures are: 1 ) Maximum Likelihood, with and without measurement errors and incorporating Bayesian priors, 2) Generalized Method of Moments, 3) Simulated Method of Moments, and 4) Indirect Inference. Monte Carlo analysis indicates that all procedures deliver reasonably good estimates under the null hypothesis. However, there are substantial differences in statistical and computational efficiency in the small samples currently available to estimate DSGE models. GMM and SMM appear to be more robust to misspecification than the alternative procedures. The implications of the stochastic singularity of DSGE models for each estimation method are fully discussed.

Monte Carlo Tests with Nuisance Parameters: A General Approach to Finite-Sample Inference and Nonstandard Asymptotics

The technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] provides an attractive method of building exact tests from statistics whose finite sample distribution is intractable but can be simulated (provided it does not involve nuisance parameters). We extend this method in two ways: first, by allowing for MC tests based on exchangeable possibly discrete test statistics; second, by generalizing the method to statistics whose null distributions involve nuisance parameters (maximized MC tests, MMC). Simplified asymptotically justified versions of the MMC method are also proposed and it is shown that they provide a simple way of improving standard asymptotics and dealing with nonstandard asymptotics (e.g., unit root asymptotics). Parametric bootstrap tests may be interpreted as a simplified version of the MMC method (without the general validity properties of the latter).

Exact Multivariate Tests of Asset Pricing Models with Stable Asymmetric Distributions

In this paper, we propose exact inference procedures for asset pricing models that can be formulated in the framework of a multivariate linear regression (CAPM), allowing for stable error distributions. The normality assumption on the distribution of stock returns is usually rejected in empirical studies, due to excess kurtosis and asymmetry. To model such data, we propose a comprehensive statistical approach which allows for alternative - possibly asymmetric - heavy tailed distributions without the use of large-sample approximations. The methods suggested are based on Monte Carlo test techniques. Goodness-of-fit tests are formally incorporated to ensure that the error distributions considered are empirically sustainable, from which exact confidence sets for the unknown tail area and asymmetry parameters of the stable error distribution are derived. Tests for the efficiency of the market portfolio (zero intercepts) which explicitly allow for the presence of (unknown) nuisance parameter in the stable error distribution are derived. The methods proposed are applied to monthly returns on 12 portfolios of the New York Stock Exchange over the period 1926-1995 (5 year subperiods). We find that stable possibly skewed distributions provide statistically significant improvement in goodness-of-fit and lead to fewer rejections of the efficiency hypothesis.

Finite-Sample Simulation-Based Inference in VAR Models with Applications to Order Selection and Causality Testing

Statistical tests in vector autoregressive (VAR) models are typically based on large-sample approximations, involving the use of asymptotic distributions or bootstrap techniques. After documenting that such methods can be very misleading even with fairly large samples, especially when the number of lags or the number of equations is not small, we propose a general simulation-based technique that allows one to control completely the level of tests in parametric VAR models. In particular, we show that maximized Monte Carlo tests [Dufour (2002)] can provide provably exact tests for such models, whether they are stationary or integrated. Applications to order selection and causality testing are considered as special cases. The technique developed is applied to quarterly and monthly VAR models of the U.S. economy, comprising income, money, interest rates and prices, over the period 1965-1996.

Étude empirique de distributions associées à la Fonction de Pénalité Escomptée

On présente une nouvelle approche de simulation pour la fonction de densité conjointe du surplus avant la ruine et du déficit au moment de la ruine, pour des modèles de risque déterminés par des subordinateurs de Lévy. Cette approche s'inspire de la décomposition "Ladder height" pour la probabilité de ruine dans le Modèle Classique. Ce modèle, déterminé par un processus de Poisson composé, est un cas particulier du modèle plus général déterminé par un subordinateur, pour lequel la décomposition "Ladder height" de la probabilité de ruine s'applique aussi. La Fonction de Pénalité Escomptée, encore appelée Fonction Gerber-Shiu (Fonction GS), a apporté une approche unificatrice dans l'étude des quantités liées à l'événement de la ruine été introduite. La probabilité de ruine et la fonction de densité conjointe du surplus avant la ruine et du déficit au moment de la ruine sont des cas particuliers de la Fonction GS. On retrouve, dans la littérature, des expressions pour exprimer ces deux quantités, mais elles sont difficilement exploitables de par leurs formes de séries infinies de convolutions sans formes analytiques fermées. Cependant, puisqu'elles sont dérivées de la Fonction GS, les expressions pour les deux quantités partagent une certaine ressemblance qui nous permet de nous inspirer de la décomposition "Ladder height" de la probabilité de ruine pour dériver une approche de simulation pour cette fonction de densité conjointe. On présente une introduction détaillée des modèles de risque que nous étudions dans ce mémoire et pour lesquels il est possible de réaliser la simulation. Afin de motiver ce travail, on introduit brièvement le vaste domaine des mesures de risque, afin d'en calculer quelques unes pour ces modèles de risque. Ce travail contribue à une meilleure compréhension du comportement des modèles de risques déterminés par des subordinateurs face à l'éventualité de la ruine, puisqu'il apporte un point de vue numérique absent de la littérature.

Promoting while checking self-interest : a conflict-based governance approach to rebalance corporate power disequilibria in Canada and the United States

La délégation du pouvoir de gestion aux administrateurs et aux gestionnaires, une caractéristique intrinsèque à la gestion efficace de grandes entreprises dans un contexte de capitalisme, confère une grande discrétion à l’équipe de direction. Cette discrétion, si elle n’est pas surveillée, peut mener à des comportements opportunistes envers la corporation, les actionnaires et les autres fournisseurs de capital qui n’ont pas de pouvoir de gestion. Les conflits entre ces deux classes d’agents peuvent émerger à la fois de décisions de gouvernance générale ou de transactions particulières (ie. offre publique d’achat). Dans les cas extrêmes, ces conflits peuvent mener à la faillite de la firme. Dans les cas plus typiques, ils mènent l’extraction de bénéfices privés pour les administrateurs et gestionnaires, l’expropriation des actionnaires, et des réductions de valeur pour la firme. Nous prenons le point de vue d’un petit actionnaire minoritaire pour explorer les méchanismes de gouvernance disponibles au Canada et aux États‐Unis. Après une synthèse dans la Partie 1 des théories sous‐jacentes à l’étude du pouvoir dans la corporation (séparation de la propriété et du contrôle et les conflits d’agence), nous concentrons notre analyse dans la Partie 2 sur les différents types de méchanismes (1) de gouvernance interne, (2) juridiques et (3) marchands, qui confèrent du pouvoir aux deux classes d’agents. Nous examinons comment les intérêts de ces deux classes peuvent être réalignés afin de prévenir et résoudre les conflits au sein de la firme. La Partie 3 explore un équilibre dynamique de pouvoir corporatif qui cherche à minimiser le potentiel d’opportunisme toute en préservant une quantité de discrétion suffisante pour la gestion efficace de la firme. Nous analysons des moyens pour renforcer les protections des actionnaires minoritaires et proposons un survol des pistes de réforme possibles.