The Effects of Credit Risk on Dynamic Portfolio Management: A New Computational Approach

The study investigates the role of credit risk in a continuous time stochastic asset allocation model, since the traditional dynamic framework does not provide credit risk flexibility. The general model of the study extends the traditional dynamic efficiency framework by explicitly deriving the optimal value function for the infinite horizon stochastic control problem via a weighted volatility measure of market and credit risk. The model's optimal strategy was then compared to that obtained from a benchmark Markowitz-type dynamic optimization framework to determine which specification adequately reflects the optimal terminal investment returns and strategy under credit and market risks. The paper shows that an investor's optimal terminal return is lower than typically indicated under the traditional mean-variance framework during periods of elevated credit risk. Hence I conclude that, while the traditional dynamic mean-variance approach may indicate the ideal, in the presence of credit-risk it does not accurately reflect the observed optimal returns, terminal wealth and portfolio selection strategies.

Nonpoint Pollution Control: Inducing First-best Outcomes through the Use of Threats

In this paper we develop a simple economic model to analyze the use of a policy that combines a voluntary approach to controlling nonpoint-source pollution with a background threat of an ambient tax if the voluntary approach is unsuccessful in meeting a pre-specified environmental goal. We first consider the case where the policy is applied to a single farmer, and then extend the analysis to the case where the policy is applied to a group of farmers. We show that in either case such a policy can induce cost-minimizing abatement without the need for farm-specific information. In this sense, the combined policy approach is not only more effective in protecting environmental quality than a pure voluntary approach (which does not ensure that water quality goals are met) but also less costly than a pure ambient tax approach (since it entails lower information costs). However, when the policy is applied to a group of farmers, we show that there is a potential tradeoff in the design of the policy. In this context, lowering the cutoff level of pollution used for determining total tax payments increases the likely effectiveness of the combined approach but also increases the potential for free riding. By setting the cutoff level equal to the target level of pollution, the regulator can eliminate free riding and ensure that cost-minimizing abatement is the unique Nash equilibrium under which the target is met voluntarily. However, this cutoff level also ensures that zero voluntary abatement is a Nash equilibrium. In addition, with this cutoff level the equilibrium under which the target is met voluntarily will not strictly dominate the equilibrium under which it is not. We show that all results still hold if the background threat instead takes the form of reducing government subsidies if a pre-specified environmental goal is not met.