DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment

Using an additive super-efficiency data envelopment analysis (DEA) model, this paper develops a new assessment index based on two frontiers for predicting corporate failure and success. The proposed approach is applied to a random sample of 1001 firms, which is composed of 50 large US bankrupt firms randomly selected from Altman's bankruptcy database and 901 healthy matching firms. This sample represents the largest firms that went bankrupt over the period 1991–2004 and represents a full spectrum of industries. Our findings demonstrate that the DEA model is relatively weak in predicting corporate failures compared to healthy firm predictions, and the assessment index improves this weakness by giving the decision maker various options to achieve different precision levels of bankrupt, non-bankrupt, and total predictions.     

OLIGOPOLY CAPITALISM, LABOR ORGANIZATION, AND WAGES OF WORKERS IN AMERICAN MANUFACTURING INDUSTRIES

This article investigates the interaction between oligopoly power, labor unionization, and worker wages. Using data from the Panel Study of Income Dynamics for workers in manufacturing industries little evidence is found that workers are exploited by oligopolistic employers, but rather wages for production workers increase with both unionization and employer's market power. There is evidence, however, that unionization reduces variation in wages due to increased oligopoly power.     

Children's Career Development: Metaphorical Images of Theory,Research, and Practice

This summative article discusses 5 invited contributions on children's career development. The authors of these articles were asked to consider the status quo of children's career development, issues facing this field, and future directions. Several emergent themes focused on theory, research, and practice and their interactive potential in children's career development. Suggestions for future direction in the study of children's career development include the need for greater contextualization and interdisciplinary collaboration, the revision and innovation of theory, and the need for organizing frameworks for theory, research, and practice.     

Lest power be forgotten: networks, division and difference in the city

Over the last decade we have seen a notable shift in the urban Society literature from discourses of division to discourses of difference. This shift has opened up new ways of understanding the complexities of city life and the formation of heterogeneous subjectivities and identities in the spaces of the city. There has been, we argue, a worrying tendency in this process to lose an analysis of the workings of power, While early Marxist, feminist and race/ethnicity debates were firmly located within a framework which highlighted power, post‐structuralist debates have operated with a more fluid notion of power, which at times has become so fluid as to evaporate into thin air. Our intention here in to re‐emphasise the significance of power while holding on to the concept of difference. We do this by using the notion of power networks that operate at different temporal and spatial scales. These give the city contrasting spatialities and temporalities that overlap one another. The city is seen as a palimpsest of time‐space networks that capture some of the presence of difference as well as suggesting its absences. These time‐space networks of power are considered in the material, perceived and imaginary realms in relation to bodies, interests and symbols.     

An influence method for outlier detection applied to time series traffic data

The work of Chernick et al. (1982) is extended to form a quantitative outlier detection statistic for use with time series data. The statistic is formed from the squared elements of the influence function matrix, where each element of the matrix gives the influence on the theoretical autocorrelation function at lag k (pk) of a pair of obser vations at time lag k. The approximate first four moments for the statistic are derived and, by fitting Johnson curves to these theoretical moments, critical points are also produced. The statistic is also used to form the basis of an adjustment procedure to treat outliers or estimate missing values in the time series. The nuclear power data of Chernick et al. and the traffic count data of the Department of Transport are used for practical illustration.     

Dealing with Ties in Failure Time Data

In dealing with ties in failure time data the mechanism by which the data are observed should be considered. If the data are discrete, the process is relatively simple and is determined by what is actually observed. With continuous data, ties are not supposed to occur, but they do because the data are grouped into intervals (even if only rounding intervals). In this case there is actually a non–identifiability problem which can only be resolved by modelling the process. Various reasonable modelling assumptions are investigated in this paper. They lead to better ways of dealing with ties between observed failure times and censoring times of different individuals. The current practice is to assume that the censoring times occur after all the failures with which they are tied.