Mark M. Westerfield

The Size and Specialization of Direct Investment Portfolios

Existing models of the size and scope of investment activity traditionally assume an infinite pool of ex-ante identical projects, despite the fact that managers often face a limited choice of projects that vary in quality. In this paper, we investigate optimal project selection in a model in which a portfolio manager observes a limited pool of heterogeneous investment opportunities. We use an order statistics argument to derive predictions on the size and scope of the investment portfolio. Counter to existing models, we show that the number and specialization of investments within a portfolio are substitutes; variables that increase (decrease) the set of available projects or returns to investment activity, such as skill (competition) cause the portfolio to be larger (smaller) and more generalized (specialized). We test our models predictions and document new stylized facts in a setting with highly skewed payoffs, formalized specialization, and a high shadow cost of access to potential projects: the U.S. venture capital industry.

Optimal Dynamic Contracts with Moral Hazard and Costly Monitoring

We introduce a tractable dynamic monitoring technology into a continuous-time moral-hazard problem and study the optimal long-term contract between principal and agent. Monitoring adds value by allowing the principal to reduce the intensity of performance-based incentives, reducing the likelihood of costly termination. We present a novel characterization of optimal dynamic incentive provision when performance-based incentives may decline continuously to zero. Termination happens in equilibrium only if its costs are relatively low. In general, the intensity of both monitoring and performance-based compensation can be non-monotonic functions of the quality of past performance. Our results can also help explain puzzling empirical findings on the relationship between performance history and future pay-performance sensitivity and on the linkage between termination, performance, and monitoring. We also discuss implications of our model for optimal security design and endogenous financing constraints.