Elliptically contoured model and factorization of wllks1 A

In a series of papers, Kshirsagar (1964, 1971) and McHenry and Kshirsagar (1977), factorize Wilks' A into a number of factors and find the independent null multivariate beta densities of these factors. These factors are the likelihood ratio test criteria for testing the goodness of fit of certain assigned discriminant functions or canonical variables either in the space of independent or dependent variables. Essentially the factors of Wilks' A are the factors of certain multivariate beta distributed matrix or its determinant. The Bartlett decomposition of the underlying multivariate beta distribution into independent factors determines the distribution of these factors. The present paper generalizes Kshirsagar's (1971) normal theory to the elliptically contoured model, and shows that his results are null robust for the elliptically contoured model.     

Infiuence functions for certain parameters in discriminant analysis when a single discriminant function is not adequate

The influence function introduced by Hampel (1968, 1973, 1974) i s a tool that can be used for outlier detection. Campbell (1978) has derived influence function for ~ahalanobis's distance between two populations which can be used for detecting outliers i n discriminant analysis. Radhakrishnan and Kshirsagar (1981) have obtained influence functions for a variety of parametric functions i n multivariate analysis. Radhakrishnan (1983) obtained influence functions for parameters corresponding to "residual" wilks's A and i t s "direction" and "collinearity" factors i n discriminant analysis when a single discriminant function is ade- quate while discriminating among several groups. In this paper influence functions for parameters that correspond to "residual" wilks's A and its "direction" and "coplanarity" factors used to test the goodness of f i t of s (s>l) assigned discriminant func- tions for discriminating among several groups are obtained. These influence functions can be used for outlier detection i n m u l t i -variate data when a single discriminant function is not adequate.     

Bias correction and improved residuals for non-exponential family nonlinear models

In this paper we derive general formulae for the biases to order n ^?1 of the parameter estimates in a general class of nonlinear regression models, where n is the sample size. The formulae are related to those of Cordeiro and McCullagh (1991) and Paula (1992) and may be viewed as extensions of their results, Correction factors are derived for the score and deviance component residuals in these models. The practical use of such corrections is illustrated for the log-gamma model.     

Great Expectatrics: Great Papers,Great Journals,Great Econometrics

The article discusses alternative Research Assessment Measures (RAM), with an emphasis on the Thomson Reuters ISI Web of Science database (hereafter ISI). Some analysis and comparisons are also made with data from the SciVerse Scopus database. The various RAM that are calculated annually or updated daily are defined and analyzed, including the classic 2-year impact factor (2YIF), 2YIF without journal self-citations (2YIF*), 5-year impact factor (5YIF), Immediacy (or zero-year impact factor (0YIF)), Impact Factor Inflation (IFI), Self-citation Threshold Approval Rating (STAR), Eigenfactor score, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, Zinfluence, and PI-BETA (Papers Ignored – By Even The Authors). The RAM are analyzed for 10 leading econometrics journals and 4 leading statistics journals. The application to econometrics can be used as a template for other areas in economics, for other scientific disciplines, and as a benchmark for newer journals in a range of disciplines. In addition to evaluating high quality research in leading econometrics journals, the paper also compares econometrics and statistics, alternative RAM, highlights the similarities and differences of the alternative RAM, finds that several RAM capture similar performance characteristics for the leading econometrics and statistics journals, while the new PI-BETA criterion is not highly correlated with any of the other RAM, and hence conveys additional information regarding RAM, highlights major research areas in leading journals in econometrics, and discusses some likely future uses of RAM, and shows that the harmonic mean of 13 RAM provides more robust journal rankings than relying solely on 2YIF.     

VARIATION REDUCTION AND ROBUST DESIGNS

In this paper we consider two strategies for variation reduction. One of them is the exploitation of interactions. We also discuss the role of experiments in discovering interactions and in particular the use of robust designs to obtain the interaction between control and noise factors. Then we attempt to reduce the variation in a measurement system using a robust design.     

The Gaussian Mixture Dynamic Conditional Correlation Model: Parameter Estimation,Value at Risk Calculation,and Portfolio Selection

A multivariate generalized autoregressive conditional heteroscedasticity model with dynamic conditional correlations is proposed, in which the individual conditional volatilities follow exponential generalized autoregressive conditional heteroscedasticity models and the standardized innovations follow a mixture of Gaussian distributions. Inference on the model parameters and prediction of future volatilities are addressed by both maximum likelihood and Bayesian estimation methods. Estimation of the Value at Risk of a given portfolio and selection of optimal portfolios under the proposed specification are addressed. The good performance of the proposed methodology is illustrated via Monte Carlo experiments and the analysis of the daily closing prices of the Dow Jones and NASDAQ indexes.     

Nationalism versus civilisations: an assessment of alternate theories on the future of ethnic identity and conflict

The end of the Cold War has caused a reassessment of the future basis for conflict and identity. While Samuel Huntington predicts that super-national ‘civilisations’ are becoming the basis for identity and conflict, many dispute this arguing that either past ethnic and national bases for identity and conflict will remain the norm or that world integration and interdependence will cause the world to unite. This article examines an aspect of this debate using data on ethnic conflict from the Minorities at Risk data set, as well as data collected independently. Specifically, it assesses whether post-Cold War ethnic conflict, and by inference ethnic identity, is more influenced by civilisational or ethnic variables. The analysis shows that separatism, a nationalist variable, is considerably more strongly associated with ethnic rebellion than are civilisational differences. Furthermore, in the multi-variate analysis civilisational differences are, if anything, associated with less ethnic rebellion. Also, separatism and various political variables more strongly influence ethnic rebellion than do civilisational differences. Thus, this study strongly supports the contention that, at least as of the late 1990s, identity continues to be based on national end ethnic factors rather than civilisational ones.     

Identifying Dispersion Effects in Robust Design Experiments—Issues and Improvements

The two experimental methods most commonly used for reducing the effect of noise factors on a response of interest Y aim either to estimate a model of the variability (V(Y), or an associated function), that is transmitted by the noise factors, or to estimate a model of the ratio between the response (Y) and all the control and noise factors involved therein. Both methods aim to determine which control factor conditions minimise the noise factors' effect on the response of interest, and a series of analytical guidelines are established to reach this end. Product array designs allow robustness problems to be solved in both ways, but require a large number of experiments. Thus, practitioners tend to choose more economical designs that only allow them to model the surface response for Y. The general assumption is that both methods would lead to similar conclusions. In this article we present a case that utilises a design based on a product design and for which the conclusions yielded by the two analytical methods are quite different. This example casts doubt on the guidelines that experimental practice follows when using either of the two methods. Based on this example, we show the causes behind these discrepancies and we propose a number of guidelines to help researchers in the design and interpretation of robustness problems when using either of the two methods.     

完全经济效益的研究——兼论提高经济效益的途径

在文献[1]的基础上提出了完全经济效益系数的概念,建立了计算公式,分析了影响完全经济效益系数的因素,讨论了提高完全经济效益的一些途径,建立了完全经济效益系数变动的基本方程,讨论了生产要素系数变动的影响力。