Collateral, default penalties and almost finite-time solvency

We argue that it is possible to adapt the approach of imposing restrictions on available plans through finitely effective debt constraints, introduced by Levine and Zame (1996), to encompass models with default and collateral. Along this line, we introduce in the setting of Araujo, Páscoa and Torres-Martínez (2002) and Páscoa and Seghir (2008) the concept of almost finite-time solvency. We show that the conditions imposed in these two papers to rule out Ponzi schemes implicitly restrict actions to be almost finite-time solvent. We define the notion of equilibrium with almost finite-time solvency and look on sufficient conditions for its existence. Assuming a mild assumption on default penalties, namely that agents are myopic with respect to default penalties, we prove that existence is guaranteed (and Ponzi schemes are ruled out) when actions are restricted to be almost finite-time solvent. The proof is very simple and intuitive. In particular, the main existence results in Araujo et al. (2002) and Páscoa and Seghir (2008) are simple corollaries of our existence result.

Infrastructure privatization in a neoclassical economy : macroeconomic impact and welfare computation

In this paper a competitive general equilibrium model is used to investigate the welfare and long run allocation impacts of privatization. There are two types of capital in this model economy, one private and the other initially public ("infrastructure"), and a positive externality due to the latter is assumed. A benevolent government can improve upon decentralized allocation internalizing the externality, but it introduces distortions in the economy through the finance of its investments. It is shown that even making the best case for public action - maximization of individuals' welfare, no• operation inefficiency and free supply to society of infrastructure services - privatization is welfare improving for a large set of economies. Hence, arguments against privatization based solely on under-investment are incorrect, as this maybe the optimal action when the financing of public investment are considered. When operation inefficiency is introduced in the public sector, gains from privatization are much higher and positive for most reasonable combinations of parameters .

The finite-sample size of the BDS test for GARCH standardized residuals

This paper uses a multivariate response surface methodology to analyze the size distortion of the BDS test when applied to standardized residuals of rst-order GARCH processes. The results show that the asymptotic standard normal distribution is an unreliable approximation, even in large samples. On the other hand, a simple log-transformation of the squared standardized residuals seems to correct most of the size problems. Nonethe-less, the estimated response surfaces can provide not only a measure of the size distortion, but also more adequate critical values for the BDS test in small samples.

Infrastructure privatization in a neoclassical economy: macroeconomic impact and welfare computation

In this paper a competi tive general equilibrium model is used to investigate the welfare and long run allocation impacts of privatization. There are two types of capital in this model economy, one private and the other initially public ("infrastructure"), and a positive extemality due to the latter is assumed. A benevolent governrnent can improve upon decentralized allocation intemalizing the extemality, but it introduces distortions in the economy through the finance of its investments. It is shown that even making the best case for public action - maximization of individuais' welfare, no operation inefficiency and free supply to society of infrastructure services - privatization is welfare improving for a large set of economies. Hence, arguments against privatization based solely on under-investment are incorrect, as this maybe the optimal action when the financing of public investment are considered. When operation inefficiency is introduced in the public sector, gains from privatization are much higher and positive for most reasonable combinations of parameters.

Convergence analysis of sampling-based decomposition methods for risk-averse multistage stochastic convex programs

We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.