Knowledge that Transforms

This paper suggests that the pure-play technique can be used in conjunction with the capital asset pricing model to determine the cost of equity capital for the divisions of a multidivision firm. Since the beta for a division is unobservable in the marketplace, a proxy beta derived from a publicly traded firm whose operations are as similar as possible to the division in question is used as the measure of the division's systematic risk. To provide empirical support for using the pure-play technique, a sample of multidivision firms and pure-play associated with each division is examined. It is shown that an appropriately weighted average of the betas of the pure-play firms closely approximates the beta of the multidivision firm.

Building on the stochastic dominance framework, time dominance efficiency analysis provides similar rules for a partial ordering of temporal prospects. Time dominance does not require any quantitative information about temporal preferences for screening decision alternatives according to their net present values. A binary time dominance proposition extends recent sufficient conditions and adds necessity. The paper's main contribution is the development of set time dominance. By eliminating binary undominated projects which no one would choose, set time dominance minimizes time efficient sets without imposing further preference assumptions.

A mean‐variance risk‐return tradeoff relationship is derived for the diffusion process limiting case of a state‐preference model, with aggregate consumption serving as a pivotal variable. The model is compared to other recent models along the dimensions of generality and tractable implementation. The incorporation of stochastic interest rates in general equilibrium and arbitrage‐based valuation models is examined, and an extension to earlier methods is discussed, in connection with the implementation of “robust” general valuation procedures.

This paper addresses the question of how government mission‐oriented R & D spending affects private R & D spending and thereby the total investment in technology. The problem is approached within the context of the capital asset pricing model in which the firm views investment projects in terms of their risk and return characteristics. The firm is assumed to produce jointly an established product and an R & D‐intensive product, where the latter generates an additional output of technology, or spillover, that is used as an input into the former. By investing in R & D the firm alters its risk and return characteristics in two ways: through the expected profits from the sale of the R & D‐intensive good; and through the expected profits from the spillover. In this model, government mission‐oriented R & D contracting affects the firm by enabling it to separate to some extent these two sources of risk and return. The main implication of the analysis is that while some public crowding out of private R & D is likely, this is almost certain to be incomplete. The empirical evidence from the U.S. transport industry supports the model and suggests that each dollar of government funding adds around 92 cents to total R & D spending; crowding out private investment by as little as eight percent.