Human Resource Management’s Effects on Firm‐Level Relative Efficiency

Using stochastic frontier production functions methodology with data from 1579 private‐sector establishments, we demonstrate that HR practices are significantly associated with differences in relative firm‐level efficiency. Supplemental analysis implies that this efficiency analysis is substantively different than the common approach to evaluating HRM’s relationships with firm‐level labor productivity. The results suggest that HR practices’ contributions to relative firm‐level efficiency are an important but heretofore overlooked factor in the relationship between HRM and firm performance.     

Perceptions of the discount retailer: an analysis of consumers' and managers' ideal discount store

Consumers' and managers' perceived images of three discount department stores and a hypothetical ideal discount store were compared in this study. Results indicate that managers and consumers possess significantly different overall impressions of each store. Significant differences were also identified between the ideal amount of each attribute and the amount offered by the retailer.     

Divergence of Cash Flow and Voting Rights,Opacity, and Stock Price Crash Risk: International Evidence

This study investigates whether and how the deviation of cash flow rights (ownership) from voting rights (control), or simply the ownership‐control wedge, influences the likelihood that extreme negative outliers occur in stock return distributions, which we refer to as stock price crash risk. We do so using a comprehensive panel data set of firms with a dual‐class share structure from 20 countries around the world for the period of 1995–2007. We predict and find that opaque firms with a large wedge are more crash prone than opaque firms with a small wedge. In addition, we predict and find that the positive relation between the wedge and crash risk is less pronounced for firms with more effective external monitoring and for firms with greater growth opportunities. The results of this study are broadly consistent with Jin and Myers’s theory that agency costs, combined with opacity, exacerbate stock price crash risk.     

Three‐Regime Asymmetric STAR Modeling and Exchange Rate Reversion

The breakdown of the Bretton Woods system and the adoption of generalized floating exchange rates ushered in a new era of exchange rate volatility and uncertainty. This increased volatility leads economists to search for economic models able to describe observed exchange rate behavior. In the present paper, we propose more general STAR transition functions that encompass both threshold nonlinearity and asymmetric effects. Our framework allows for a gradual adjustment from one regime to another and considers threshold effects by encompassing other existing models, such as TAR models. We apply our methodology to three different exchange rate data sets: one for developing countries and official nominal exchange rates, the second for emerging market economies using black market exchange rates, and the third for OECD economies.     

Labor and Corporate Governance: International Evidence from Restructuring Decisions

Our results highlight the importance of interaction among management, labor, and investors in shaping corporate governance. We find that strong union laws protect not only workers but also underperforming managers. Weak investor protection combined with strong union laws are conducive to worker–management alliances, wherein poorly performing firms sell assets to prevent large-scale layoffs, garnering worker support to retain management. Asset sales in weak investor protection countries lead to further deteriorating performance, whereas in strong investor protection countries they improve performance and lead to more layoffs. Strong union laws are less effective in preventing layoffs when financial leverage is high.     

Ordinal Pairwise Partitioning (OPP) Approach to Neural Networks Training in Bond rating

Statistical classification methods such as multivariate discriminant analysis have been widely used in bond rating classification in spite of the limitations of the methodology. Recently, neural networks have emerged as new methods for business classification. This approach to neural networks training is to categorize a new instance as one of the predefined bond classes. Such a conventional approach has limitations in dealing with the ordinal nature of bond rating. In addition, most of the prior studies have used sample data which are evenly divided among the classes. However, the natural population in real application is usually unevenly divided among the classes. Under such circumstances, it is hard to achieve good predictive performance. As the number of classes to be recognized increases, the predictive performance decreases. In this article, to increase the predictive performance in real-world bond rating, we propose the ordinal pairwise partitioning (OPP) approach to backpropagation neural networks training. The main idea of the OPP approach is to partition the data set in the ordinal and pairwise manner according to the output classes. Then, each backpropagation neural networks model is trained by using each partitioned data set and is separately used for classification. Experimental results show that the predictive performance of the proposed OPP approach can be significantly enhanced, when compared to the conventional neural networks modeling approach as well as multivariate discriminant analysis. The OPP approach has two computation methods, and we discuss under which circumstances one method performs better than the other. We also show the generalizability of the OPP approach. © 1997 by John Wiley & Sons, Ltd.     

THE IMPACT OF INITIAL FINANCIAL STATE ON FIRM DURATION ACROSS ENTRY COHORTS*

Recent theories of industry dynamics emphasize the role of financial frictions in determining post entry performance of firms. Testing these theories has been difficult because of the lack of financial data on small, young and private firms. Using a unique data set, T2LEAP, this paper considers the survival of new firms in Canadian manufacturing from a financial perspective. Duration analysis quantifies the effects of firm, industry and aggregate factors. Findings show that nonlinear effects are found with firm leverage. Finally, likelihood decompositions offer insights into the contributing factors to firm hazard for nine entry cohorts during the period 1985–1997.