Recent Bankruptcy History-Related Articles of Interest Available for Downloading from SSRN
The following bankruptcy history-related papers, arranged by abstract ID number, can be downloaded from the Social Science Research Network:
American University's Mary Hansen and Univ. of Mary Washington's Bradley Hansen: "Path Dependence in the Development of U.S. Bankruptcy Law, 1880-1938." (Abstract ID: 909294)
Rutgers University's Paul J. Miranti Jr. and Drexel University's Nandini Chandar: "Information, Institutions and Agency: The Crisis of Railroad Finance in the 1890s and the Evolution of Corporate Oversight Capabilities." (Abstract ID: 899415)
UW-Madison's Jodi L. Bellovary and Marquette University's Don E. Giacomino and Michael D. Akers: "A Review of Bankruptcy Prediction Studies: 1930 to Present." (Abstract ID: 892160)
Abstracts for each of these papers follow:
Mary Hansen and Bradley Hansen, "Path Dependence in the Development of U.S. Bankruptcy Law, 1880-1938." (Abstract ID: 909294):
We illustrate mechanisms that can give rise to path dependence in legislation. Specifically, we show how debtor-friendly bankruptcy law arose in the United States as a result of a path dependent process. The 1898 Bankruptcy Act was not regarded as debtor-friendly at the time of its enactment, but the enactment of the law gave rise to changes in interest groups, changes in beliefs about the purpose of bankruptcy law, and changes in the Democratic Party's position on bankruptcy that set the United States on a path to debtor-friendly bankruptcy law. An analysis of the path dependence of bankruptcy law produces an interpretation that is more consistent with the evidence than the conventional interpretation that debtor-friendliness in bankruptcy law began with political compromises to obtain the 1898 Bankruptcy Act.
Paul J. Miranti Jr. and Nandini Chandar, "Information, Institutions and Agency: The Crisis of Railroad Finance in the 1890s and the Evolution of Corporate Oversight Capabilities." (Abstract ID: 899415):
Using a broad socio-economic conception of capital markets agency relationships, this study analyzes an immportant economic transition in US economic history. It focuses on the institutional and informational changes that attended the reform of corporare governance and regulation in the railroad industry during the three decades following the depression of 1893 which was marked by extensive bankruptcy in the nation's largest business sector, the railroads. Institutional and social responses to his crisis provide a rich source for understanding the evolution of property rights and arrangements for enhancing corporate transparency and captial market efficiency. This study emphasizes the notion of path-dependent learning as a driver of institutional evolution. It notes that instituional responses were not limited to simple short-term, firm-specific relationships as is often usefully addressed by modern agency approahces. It also encompasses a variety of social, institutional and environmental factors that are often central in explaining the dynamic nature of organizations, capital markets and financial reporting.
Jodi L. Bellovary, Don E. Giacomino, and Michael D. Akers, "A Review of Bankruptcy Prediction Studies: 1930 to Present." (Abstract ID: 892160):
One of the most well-known bankruptcy prediction models was developed by Altman  using multivariate discriminant analysis. Since Altman’s model, a multitude of bankruptcy prediction models have flooded the literature. The primary goal of this paper is to summarize and analyze existing research on bankruptcy prediction studies in order to facilitate more productive future research in this area. This paper traces the literature on bankruptcy prediction from the 1930’s, when studies focused on the use of simple ratio analysis to predict future bankruptcy, to present. The authors discuss how bankruptcy prediction studies have evolved, highlighting the different methods, number and variety of factors, and specific uses of models.
Analysis of 165 bankruptcy prediction studies published from 1965 to present reveals trends in model development. For example, discriminant analysis was the primary method used to develop models in the 1960’s and 1970’s. Investigation of model type by decade shows that the primary method began to shift to logit analysis and neural networks in the 1980’s and 1990’s. The number of factors utilized in models is also analyzed by decade, showing that the average has varied over time but remains around 10 overall.
Analysis of accuracy of the models suggests that multivariate discriminant analysis and neural networks are the most promising methods for bankruptcy prediction models. The findings also suggest that higher model accuracy is not guaranteed with a greater number of factors. Some models with two factors are just as capable of accurate prediction as models with 21 factors.
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© Steve Jakubowski 2006