872 resultados para bankruptcy costs


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Emerging market countries that have improved institutions and attained intermediate levels of institutional quality have experienced severe financial crises following capital flow reversals. However, there is also evidence that countries with strong institutions and deep capital markets are less affected by external shocks. We reconcile these two observations using a calibrated DSGE model that extends the financial accelerator framework developed in Bernanke, Gertler, and Gilchrist (1999). The model captures financial market institutional quality with creditors. ability to recover assets from bankrupt firms. Bankruptcy costs affect vulnerability to sudden stops directly but also indirectly by affecting the degree of liability dollarization. Simulations reveal an inverted U-shaped relationship between bankruptcy recovery rates and the output loss following sudden stops. We provide empirical evidence that this non-linear relationship exists.

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The purpose of this paper is to understand whether multinational restaurant firms (MNRF’s) have higher agency and expected bankruptcy costs. Given this expectation, this may have an impact on the amount of debt incurred by MNRF’s. Overall, the findings are consistent with the existing literatue in terms of the positive relationship between MNRF’s and agency and bankruptcy cost. However, it was found that MNRF’s also have more total debt. This is surprising given the higher agency and bankruptcy costs. The importance of this research is that there may be considerations other than agency and bacnkruptcy costs affecting the capital structure decisions of MNRF’s.

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apresentado ao Instituto de Contabilidade e Administração do Porto para a Dissertação de Mestrado para obtenção do grau de Mestre em Contabilidade e Finanças sob orientação do Mestre Adalmiro Álvaro Malheiro de Castro Andrade Pereira

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The capital structure and regulation of financial intermediaries is an important topic for practitioners, regulators and academic researchers. In general, theory predicts that firms choose their capital structures by balancing the benefits of debt (e.g., tax and agency benefits) against its costs (e.g., bankruptcy costs). However, when traditional corporate finance models have been applied to insured financial institutions, the results have generally predicted corner solutions (all equity or all debt) to the capital structure problem. This paper studies the impact and interaction of deposit insurance, capital requirements and tax benefits on a bankÇs choice of optimal capital structure. Using a contingent claims model to value the firm and its associated claims, we find that there exists an interior optimal capital ratio in the presence of deposit insurance, taxes and a minimum fixed capital standard. Banks voluntarily choose to maintain capital in excess of the minimum required in order to balance the risks of insolvency (especially the loss of future tax benefits) against the benefits of additional debt. Because we derive a closed- form solution, our model provides useful insights on several current policy debates including revisions to the regulatory framework for GSEs, tax policy in general and the tax exemption for credit unions.

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This study takes a direct approach to determine management motivation for the use of financial derivatives. We survey a sample of Australian firms on attitudes to derivative use and financial risk management. Management views are sought on the importance of a series of theoretical reasons for using derivatives. Generally, we find that managers are focused on the broad reduction of risk and volatility of cash flows and earnings in using derivatives. Specific issues such as reducing bankruptcy costs, debt levels and taxation are not considered as important. A further interesting result from this research is that even though firms may use derivatives they may not necessarily hedge all of their annual exposures across different financial risks. This helps explain the inconsistency of results in many empirical studies on the determinants of derivative use.

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The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- Bayesian, Hazard and Mixed Logit. A salient feature of the study is that the analysis includes both parametric and nonparametric bankruptcy prediction models. A sample of firms from Lynn M. LoPucki Bankruptcy Research Database in the U. S. was used to evaluate the relative performance of the three models. The choice of a cut-off point and sampling procedures were found to affect the rankings of the various models. In general, the results indicate that the empirical cut-off point estimated from the training sample resulted in the lowest misclassification costs for all three models. Although the Hazard and Mixed Logit models resulted in lower costs of misclassification in the randomly selected samples, the Mixed Logit model did not perform as well across varying business-cycles. In general, the Hazard model has the highest predictive power. However, the higher predictive power of the Bayesian model, when the ratio of the cost of Type I errors to the cost of Type II errors is high, is relatively consistent across all sampling methods. Such an advantage of the Bayesian model may make it more attractive in the current economic environment. This study extends recent research comparing the performance of bankruptcy prediction models by identifying under what conditions a model performs better. It also allays a range of user groups, including auditors, shareholders, employees, suppliers, rating agencies, and creditors' concerns with respect to assessing failure risk.

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Farmers' exposure to pesticides is high in developing countries. As a result many farmers suffer from ill-health, both short and long term. Deaths are not uncommon. This paper addresses this issue. Field survey data from Sri Lanka are used to estimate farmers' expenditure on defensive behavior (DE) and to determine factors that influence DE. The avertive behavior approach is used to estimate costs. Tobit regression analysis is used to determine factors that influence DE. Field survey data show that farmers' expenditures on DE are low. This is inversely related to high incidence of ill health among farmers using pesticides.

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Housing affordability is gaining increasing prominence in the Australian socioeconomic landscape, despite strong economic growth and prosperity. It is a major consideration for any new development. However, it is multi-dimensional, has many facets, is complex and interwoven. One factor widely held to impact housing affordability is holding costs. Although it is only one contributor, the nature and extent of its impact requires clarification. It is certainly more multifarious than simple calculation of the interest or opportunity cost of land holding. For example, preliminary analysis suggests that even small shifts in the regulatory assessment period can significantly affect housing affordability. Other costs associated with “holding” also impact housing affordability, however these costs cannot always be easily identified. Nevertheless it can be said that ultimately the real impact is felt by those whom can least afford it - new home buyers whom can be relatively easily pushed into the realms of un-affordability.