In this paper, I examine the effects of debt structure on conservatism. The analysis is conducted in two steps. First, I examine the direction of causality between capital structure and conditional conservatism by using a unique sample of zero leverage firms that transition to non-zero leverage. Also I investigate whether off-balance-sheet leverage incrementally explains conditional conservatism. Second, I study whether the various characteristics of debt also affect conditional conservatism. Specifically, the characteristics I investigate include: (1) whether the debt is public or private, (2) maturity, (3) convertibility, (4) seniority, and (5) securitization. Since these different characteristics of debt affect agency costs to varying degrees, I predict that differences in the type of debt will lead to cross-sectional differences in conditional conservatism. I find that entering the debt market is an important factor driving demand for conditional conservatism, and that off-balance-sheet leverage incrementally increases conditional conservatism relative to on-balance-sheet leverage. Consistent with my predictions, I find that firms with greater levels of public debt, short-term debt, subordinate debt, and unsecured debt provide more timely loss recognition. After controlling for the likelihood of conversion, I also find firms with a greater level of convertible debt provide less timely loss recognition. Overall my results indicate that accounting conservatism not only varies with the presence of debt, but also with the contractual features of debt.

Using permanent income life-cycle theory, I analyze the effects of liquidity constraints on the household’s ability to smooth life time consumption due to a change in housing and stock market wealth. Using data from the Canadian national accounts and chartered bank balance sheets I test if improved access to housing wealth due to fundamental shifts to the banking industry in the 1980s has lowered liquidity constraints and improved the household’s ability to smooth consumption.

The business corporation is an important engine for the creation of wealth and it plays a vital role in promoting economic development and social progress in both domestic and international economies. Hence companies must operate within a governance framework that keeps them focused on their objectives and accountable for their actions. There is the need to establish adequate and credible governance arrangements. The degree of observance to the basic principles of good corporate governance is an important factor for investment decisions. / Traditional corporate doctrine has taken the separation of ownership from control as the core problem of corporate governance. On this view, the principal function of corporate law is to devise strategies and mechanisms to ensure that corporate decision-making is based only on shareholders' interests. However, corporate managers are subject to influence from many other sources. Thus, the study of corporate governance must take account of all factors that affect managerial decision-making. / In this thesis, I examine the influence that debt financing brings to bear on corporate governance and examine whether debt-holders should be beneficiaries of corporate fiduciary duties. I conclude that any such duty should be narrowly cast.

The thesis analyses the moral hazard problem which arises in political or fiscal federations when member states anticipate being bailed out by the centre in case of financial distress. In particular, I examine whether an orderly default mechanism or deeper fiscal integration within the European Union can alleviate the soft budget constraint phenomenon and provide a solution to the sovereign debt crises engulfing the Eurozone and other parts of the world. The first essay adapts the standard Stackelberg approach of the bailout literature in order to study the effects of bankruptcy procedures on regional opportunistic behaviour. The insolvency mechanism is shaped by two parameters: the costs of default and the exemption level for public assets. The model lends support to the market discipline hypothesis if all public assets are exempt from seizure. If, by contrast, the exemption level for public assets is low, it is the central government rather than the credit market that discourages overborrowing since the former is incentivised to tax heavily indebted regions. The model's major policy insight is that an insolvency mechanism can lower the federation's welfare if it is not carefully designed. The second essay sheds light on the incentive effects of the sovereign debt restructuring mechanism which has been drafted by the Eurozone in response to the debt crisis. Employing a global game approach, the model analyses the impact of insolvency procedures on the size of the bailout, the level of effort exerted by the debtor country and EU welfare. Challenging some arguments in the policy literature, the model's major policy implication is that a half-hearted debt restructuring mechanism fails to mitigate the commitment and moral hazard problems embedded in the current EMU framework. The third essay questions the conventional wisdom that the Euro cannot survive without closer integration, using a simple political economy framework. The model compares the stability and welfare implications of the current "muddling through" scenario, an orderly default mechanism as well as a fiscal and a political union setting. Interestingly, the results suggest that the "muddling through" scenario is not more prone to break-up than the political or the fiscal union. The model's major policy recommendation is that implementing an orderly default mechanism and inserting an explicit exit clause into the European Treaties might prove more effective in preventing a Eurozone break-up than far-reaching institutional reforms.

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Typescript. / Thesis (Ph. D.)--University of Hawaii at Manoa, 1987. / Bibliography: leaves 124-131. / Photocopy. / x, 131 leaves, bound ill. 28 cm

One of the most successful and most controversial innovative financial products in recent years has been collateralised debt obligations (CDOs). The dimensionality of dependency embedded in a typical CDO structure poses great challenges for researchers - in both generating realistic default dynamics and correlation, and in the mean time achieving fast and accurate model calibration. The research presented in this thesis contributes to the class of bottom-up models, which, as opposed to top-down models, start by modelling the individual obligor default process and then moving them up through the dependency structures to build up the loss distributions at the portfolio level. The Gaussian model (Li 2000) is a static copula model. It has only on correlation parameter, which can be calibrated to one CDO tranche at a time. Its simplicity achieves wide spread industry application even though it suffers from the problem of ’correlation smile’. In other words, it cannot fit the market in an arbitrage-free manner in the capital-structure dimension. The first contribution of this thesis is the sensitivities analysis with regard to model parameters of expected losses of CDO tranches in the Gaussian and NIG copula models. The study provided substantial insight into the essence of the dependency structure. In addition, we apply the intensity approach to credit modelling in order to imply market distributions non-parametrically in the form of a binomial lattice. Under the same framework, we developed a series of three models. The static binomial model can be calibrated to the CDS index tranches exactly, with one set of parameters. The model can be seen as a non-parametric copula model that is arbitrage free in the capital-structure dimension. Static models are not suitable to price portfolio credit derivatives that are dynamic in nature. The static model can be naturally developed into a dynamic binomial model and satisfies no-arbitrage conditions in the time dimension. This setup, however, reduces model flexibility and calibration speed. The computational complexity comes from the non-Markovian character of the default process in the dynamic model. Inspired by Mortensen (2006), in which the author defines the intensity integral as a conditioning variable, we modify the dynamic model into a Markovian model by modelling the intensity integral directly, which greatly reduces the computational time and increases model fit in calibration. We also show that, when stochastic recovery rates are involved, there is a third no-arbitrage condition for the expected loss process that needs to be built into the Markovian model. For all binomial models, we adopt a unique optimisation algorithm for model calibration - the Cross Entropy method. It is particularly advantageous in solving large-scale non-linear optimsation problems with multiple local extrema, as encountered in our model.

One of the most successful and most controversial innovative financial products in recent years has been collateralised debt obligations (CDOs). The dimensionality of dependency embedded in a typical CDO structure poses great challenges for researchers - in both generating realistic default dynamics and correlation, and in the mean time achieving fast and accurate model calibration. The research presented in this thesis contributes to the class of bottom-up models, which, as opposed to top-down models, start by modelling the individual obligor default process and then moving them up through the dependency structures to build up the loss distributions at the portfolio level. The Gaussian model (Li 2000) is a static copula model. It has only on correlation parameter, which can be calibrated to one CDO tranche at a time. Its simplicity achieves wide spread industry application even though it suffers from the problem of ’correlation smile’. In other words, it cannot fit the market in an arbitrage-free manner in the capital-structure dimension. The first contribution of this thesis is the sensitivities analysis with regard to model parameters of expected losses of CDO tranches in the Gaussian and NIG copula models. The study provided substantial insight into the essence of the dependency structure. In addition, we apply the intensity approach to credit modelling in order to imply market distributions non-parametrically in the form of a binomial lattice. Under the same framework, we developed a series of three models. The static binomial model can be calibrated to the CDS index tranches exactly, with one set of parameters. The model can be seen as a non-parametric copula model that is arbitrage free in the capital-structure dimension. Static models are not suitable to price portfolio credit derivatives that are dynamic in nature. The static model can be naturally developed into a dynamic binomial model and satisfies no-arbitrage conditions in the time dimension. This setup, however, reduces model flexibility and calibration speed. The computational complexity comes from the non-Markovian character of the default process in the dynamic model. Inspired by Mortensen (2006), in which the author defines the intensity integral as a conditioning variable, we modify the dynamic model into a Markovian model by modelling the intensity integral directly, which greatly reduces the computational time and increases model fit in calibration. We also show that, when stochastic recovery rates are involved, there is a third no-arbitrage condition for the expected loss process that needs to be built into the Markovian model. For all binomial models, we adopt a unique optimisation algorithm for model calibration - the Cross Entropy method. It is particularly advantageous in solving large-scale non-linear optimsation problems with multiple local extrema, as encountered in our model.

One of the most successful and most controversial innovative financial products in recent years has been collateralised debt obligations (CDOs). The dimensionality of dependency embedded in a typical CDO structure poses great challenges for researchers - in both generating realistic default dynamics and correlation, and in the mean time achieving fast and accurate model calibration. The research presented in this thesis contributes to the class of bottom-up models, which, as opposed to top-down models, start by modelling the individual obligor default process and then moving them up through the dependency structures to build up the loss distributions at the portfolio level. The Gaussian model (Li 2000) is a static copula model. It has only on correlation parameter, which can be calibrated to one CDO tranche at a time. Its simplicity achieves wide spread industry application even though it suffers from the problem of ’correlation smile’. In other words, it cannot fit the market in an arbitrage-free manner in the capital-structure dimension. The first contribution of this thesis is the sensitivities analysis with regard to model parameters of expected losses of CDO tranches in the Gaussian and NIG copula models. The study provided substantial insight into the essence of the dependency structure. In addition, we apply the intensity approach to credit modelling in order to imply market distributions non-parametrically in the form of a binomial lattice. Under the same framework, we developed a series of three models. The static binomial model can be calibrated to the CDS index tranches exactly, with one set of parameters. The model can be seen as a non-parametric copula model that is arbitrage free in the capital-structure dimension. Static models are not suitable to price portfolio credit derivatives that are dynamic in nature. The static model can be naturally developed into a dynamic binomial model and satisfies no-arbitrage conditions in the time dimension. This setup, however, reduces model flexibility and calibration speed. The computational complexity comes from the non-Markovian character of the default process in the dynamic model. Inspired by Mortensen (2006), in which the author defines the intensity integral as a conditioning variable, we modify the dynamic model into a Markovian model by modelling the intensity integral directly, which greatly reduces the computational time and increases model fit in calibration. We also show that, when stochastic recovery rates are involved, there is a third no-arbitrage condition for the expected loss process that needs to be built into the Markovian model. For all binomial models, we adopt a unique optimisation algorithm for model calibration - the Cross Entropy method. It is particularly advantageous in solving large-scale non-linear optimsation problems with multiple local extrema, as encountered in our model.

Thesis (M.S.)--Eastern Illinois University, 2008. / Includes bibliographical references (leaves 48-55).