We present a dynamic model of venture capital financing, described as a sequential investment problem with uncertain outcome. Each venture has a critical, but unknown threshold beyond which it cannot progress. If the threshold is reached before the completion of the project, then the project fails, otherwise it succeeds. The investors decide sequentially about the speed of the investment and the optimal path of staged investments. We derive the dynamically optimal funding policy in response to the arrival of information during the development of the venture. We develop three types of predictions from our theoretical model and test these predictions in a large sample of venture capital investments in the U.S. for the period of 1987-2002.
First, the investment flow starts low if the failure risk is high and accelerates as the projects mature. Second, the investment flow reacts positively to information that arrives while the project is developed. We find that the investment decisions are more sensitive to the information received during the development than to the information held prior to the project launch. Third, investors distribute their investments over more funding rounds if the failure risk is larger.
We consider the provision of venture capital in a dynamic model with multiple research stages, where time and investment needed to meet each benchmark are unknown. The allocation of funds is subject moral hazard. The optimal contract provides for incentive payments linked to attaining the next benchmark, which must be increasing in the funding horizon of each stage. Benchmarking reduces agency costs, directly by shortening the agent’s guaranteed funding horizon, and indirectly via an implicit incentive effect of information rents in future financing rounds.
The ex ante need to provide incentives and the venture capitalist’s desire to cut information rents ex post create a hold-up conflict, which can be overcome by providing all funds in every stage in a single up-front payment. Empirical patterns of the evolution of financing rounds and research intensity over the lifetime of a project are explained as optimal choices: the optimal capital allocated and the funding horizon are increasing from one stage to the next. This emphasizes the notion that early stages are the riskiest in an innovative venture.
This paper considers the financing of a research project under uncertainty about the time of completion and the probability of eventual success. The uncertainty about future success gradually diminishes with the arrival of addtional funding. The entrepreneur controls the funds and can divert them. We distinguish between relationship financing, meaning that the entrepreneur’s allocation of the funds is observable, and arm’s length financing, where it is unobservable.
We find that equilibrium funding stops altogether too early relative to the efficient stopping time in both financing modes. We characterize the optimal contracts and equilibrium funding decisions. The financial constraints will typically become tighter over time under relationship finance, and looser under arm’s length financing. The trade-off is that while relationship financing may require smaller information rents, arm’s length financing amounts to an implicit commitment to a finite funding horizon. The lack of such a commitment under relationship financing implies that the sustainable release of funds eventually slows down. We obtain the surprising result that arm’s length contracts are preferable in a Pareto sense.