On Upshifted Reversed Mean Residual Life Order

Recently, the concept of reversed mean residual life order based on the mean of the random variable X _t  = (t ? X | X ≤ t), t > 0, called the reversed residual life, defined for the nonnegative random variable X, has been introduced in the literature. In this paper, a stochastic order based on the shifted version of the reversed mean residual life is proposed, based on the reversed mean residual life function for a random variable X with support (l _X , ∞), where l _X may be negative infinity, and its properties are studied. Closure under the Poisson shock model and properties for spare allocation are also discussed.     

Learning organization and development of woman managers in Pakistan

Women's participation in economic activities in general and at managerial status in particular is insignificant in Pakistan. Furthermore, the opportunities for professional development of women managers are meagre because of multiple socio-cultural limitations. This paper attempts to draw a profile of female managers focusing, inter alia, on the trend and structure of women's human resource, ratio of employment, work environment and scope of development, efficiency at work, satisfaction level, professional commitment and forces inhibiting women access to jobs under the learning organization perspectives. It also exhibits issues bearing policy implications in regard to the development of women as managers and also as human resource.     

Joint modeling of longitudinal continuous,longitudinal ordinal,and time-to-event outcomes

Lifetime Data Analysis - In this paper, we propose an innovative method for jointly analyzing survival data and longitudinally measured continuous and ordinal data. We use a random effects...     

Quality of Life and Well-Being Ranking of Selected Districts of Khyber Pakhtunkhwa,Pakistan

Quality of life (QoL) is a multidimensional concept encompassing many aspects of an individual’s existence. It is not just a measure of material resources but of intangible environments which affect quality of life. The study concentrates on the province of Khyber Pakhtunkhwa, Pakistan, and looks at the QoL and well-being in thirteen districts representing the province’s major population. It followed an integrative approach to measuring quality of life. Principal component analysis was used to tackle with multidimensionality. Weighted factor scores were used as an index for ranking QoL and well-being on the basis of social indicators chosen in different life domains. The results show that districts having high urban disposition top the ranks in QoL in Khyber Pakhtunkhwa, like Peshawar, Mardan, Swat and Charsadda, while Bannu, Kohat and Lower Dir fall amongst the bottom districts in terms of QoL. The rural/urban ranking also follows similar patterns with a few exceptions.     

An empirical bayes estimate of multinomial probabilities

This paper deals with the prblem of estimating simultaneously the parameters (Cell probabilities) of m ≤ 2 independent multinomial distributions, with respect to a quadratic loss functions. An empirical Bayes estimator is proposed which is shown to have smaller risk than the maximum likelihood estimator for sufficiently large values of mq, where q is a measure of the average diversity of the given multinomial populations. Some numerical results are given on the performance of the proposed estimator.     

The Application of Neural Networks and a Qualitative Response Model to the Auditor's Going Concern Uncertainty Decision*

An auditor gives a going concern uncertainty opinion when the client company is at risk of failure or exhibits other signs of distress that threaten its ability to continue as a going concern. The decision to issue a going concern opinion is an unstructured task that requires the use of the auditor's judgment. In cases where judgment is required, the auditor may benefit from the use of statistical analysis or other forms of decision models to support the final decision. This study uses the generalized reduced gradient (GRG2) optimizer for neural network learning, a backpropagation neural network, and a logit model to predict which firms would receive audit reports reflecting a going concern uncertainty modification. The GRG2 optimizer has previously been used as a more efficient optimizer for solving business problems. The neural network model formulated using GRG2 has the highest prediction accuracy of 95 percent. It performs best when tested with a small number of variables on a group of data sets, each containing 70 observations. While the logit procedure fails to converge when using our eight variable model, the GRG2 based neural network analysis provides consistent results using either eight or four variable models. The GRG2 based neural network is proposed as a robust alternative model for auditors to support their assessment of going concern uncertainty affecting the client company.     

A Robust Multivariate Procedure for the Identification of Problem Savings and Loan Institutions*

The 1980s have seen a great increase in the number of failed savings and loan institutions. In order to prevent such failures, it would be helpful if regulators have an early warning model. Such a model should be able to flag potential failed firms to prevent failure. In this paper, a robust multivariate procedure is used to successfully identify potentially failed firms well ahead of an actual failure date.     

Testing equality of variances after a preliminary test of significance for correlation coefficient

On the basis of the outcome of a preliminary test of significance for the population correlation coefficient it is decided as to whether the variance ratio or the sample correlation coefficient between u=(x+y)/2 and v=x?y)/2 is to be used as a test statistic for testing the equality of variances. A method for determining the critical points for the preliminary test and the main test has been suggested. The power of the test procedure is compared with those of standard tests.     

Dissecting Public Sector Corruption in Bangladesh: Issues and Problems of Control

The public sector in Bangladesh is ridden with corruption of various dimensions and shades. Apart from bribery, rent-seeking and misappropriation of funds, the performance of public organizations is adversely affected by a host of other factors like excessive lobbying, delays in service provision, pilferage and larceny, irresponsible conduct of officials, bureaucratic intemperance, patronage and clientelism. The several institutional mechanisms to combat administrative malfeasance are rendered ineffective by a non-committed political leadership, a blase"d bureaucracy, weak accountability structures, and unproductive legislative labors. The public body for controlling corruption is itself associated with all sorts of malpractices and conducts its affair most unprofessionally. Despite several attempts, the constitutionally authorized ombudsman is yet to find its place in the governance framework.