Implementing Fischer Black's Simple Discounting Rule

Corporate managers typically estimate the value of capital projects by discounting the project's expected future net cash flows at the cost of capital. The capital asset pricing model (CAPM) is generally used to estimate that cost. But, as anyone who has worked on the finance or business development staff of a public company can attest, there are major challenges in applying the CAPM, including largely unresolved questions about what constitutes the “market portfolio,” how to estimate market risk premiums, and how to estimate the betas of projects. In a short article published in Financial Management in 1988, Fischer Black proposed a valuation “discounting rule” that avoids all these problems—one that involves discounting a relatively certain (as opposed to an expected or average) level of operating cash flows at the risk-free rate. But Black's article does not address the question of how to calculate these “certainty equivalent” or “conditional” cash flows. In this article, the authors propose a way of implementing Black's rule that involves estimating the “conditional” cash flows in a three-step procedure:

• • Find a benchmark security that correlates with the project's cash flows;
• • Estimate the percentiles of the distribution in which the benchmark return equals the risk-free rate over different investment horizons;
• • Use information from corporate managers to assess the cash flows that define the same percentiles in the cash flow distributions.

As the authors point out, the virtue of Black's rule is that it shifts the focus of the analyst away from the assessment of discount factors and puts it squarely on the more challenging, and arguably more relevant, problem of estimating the project's cash flows.     

The Role of Information and Influence in Social Networks

A bstract .   This article examines two mechanisms through which social networks are related to job mobility: (1) access to diverse sources of information about job openings and (2) nonredundant sources of influence. Using data on job changing and social networks among television station managers, we assess the extent to which job information and influence variables mediate the relationship between social network structure and getting a better job. Results indicate that there is an association between job mobility and having nonredundant contacts, but our measures of the information and influence mechanisms are not significant mediators. We conclude by reexamining the network-resource model that forms the basis for much of the research on the relationship between social networks and job mobility.     

Networks and linkages among firms and organizations in the Ottawa-region technology cluster

This paper reports on a study of the networking and linkage practices of technology and non-technology firms within the Ottawa cluster. The work seeks to understand how and why particular patterns of networks and linkages evolve and it examines empirically the usage and value of networks and linkages. Previous work argues that technology firms need to be relatively more adept at developing external relationships in order to be successful than do non-technology based companies. This work, however, finds that technology firms exhibit fewer linkages than non-technology based companies do within the Ottawa cluster. The research suggests that the vitality of the Ottawa cluster could be further enhanced through the promotion of additional networking and linkages among regional firms. A key implication for management practice is that CEOs of technology-based firms should work towards establishing and maintaining additional valued relationships.     

Multiple-objective methods in regulatory decision making: A conceptual framework applied to U.S. automobile safety standards

Public policy making is a complex matter. Policy makers are charged with balancing a broad spectrum of competing objectives, reflecting in varying degrees the interests and aspirations of a diverse range of constituencies and stakeholders. Policy decisions have differential impacts on differing constituencies and the contributions of these impacts to objectives are frequently uncertain, difficult to quantify, and hotly disputed. Formal methods of decision analysis have been advanced as aids for coping with complexity and have been applied to some public policy issues, most notably the management of water resources. While formal methods have the apparent benefit of rationalizing the policy process and improving the efficacy and equity of policy decisions, serious questions remain concerning the acceptability and ultimate usefulness of formal analyses in the public arena. In this article we examine these questions in the context of policy making relating to government regulation of automobile designs for safety. We consider what would be involved in attempting to use a relatively modern, multiple-objective approach in this context. The key questions are how and, more importantly, why multiple-objective methods might be used. The article begins with an illustrative case study, describes the current policymaking process, identifies the parties involved in and affected by this process, elicits key objectives, looks briefly at some scalar-objective approaches, and then outlines a multiple-objective approach. The framework developed arguably is useful in assisting policy making, at least at a qualitative level. Issues which impede a more quantitative resolution of this framework are discussed. This article is intended as a pilot study which may promote research toward the achievement of a useable multiple-objective procedure applicable in the public domain.     

Are we nice(r) to nice(r) people?—An experimental analysis

We experimentally investigate whether individuals can reliably detect cooperators (the nice(r) people) in an anonymous decision environment involving “connected games.” Participants can condition their choices in an asymmetric prisoners’ dilemma and a trust game on past individual (their partner’s donation share to a self-selected charity) and social (whether their partner belongs to a group with high or low average donations) information. Thus, the two measures of niceness are the individual donation share in the donation task, and the cooperativeness of one’s choice in the two games. We find that high donors achieve a higher-than-average expected payoff by cooperating predominantly with other high donors. Group affiliation proved to be irrelevant. Electronic Supplementary Material Supplementary material is available in the online version of this article at . JEL Classification C91, C72, D3     

Public sector health insurance trusts

Public sector associations have successfully developed and run employee health insurance pools for almost 30 years, providing members with savings and flexibility not available from commercial health insurance carriers. This article looks at the models, technical tools and governance philosophy that have contributed to their success in a very challenging business environment.     

An analysis of asymmetric demand response to price changes: The case of local telephone calls

Asymmetric demand responses to price changes are not an observable implication of classical demand theory, which predicts that consumers will react to a small price increase in much the same way as they do to a small price decrease. Yet applied researchers have long speculated that consumers are more sensitive to price increases than they are to price decreases. In addition, recent empirical studies generally support the theory of asymmetric demand responses. We construct a dynamic model based on data gathered from monthly telephone bills for 128 New York Telephone customers over a five-year period. Our results support the conclusion that customers react more quickly and strongly when prices go up than they do when prices go down.We would like to thank Manny Haas and Bernie Reddy for their comments and suggestions.     

Combining forecasts: An application to elections

We summarize the literature on the effectiveness of combining forecasts by assessing the conditions under which combining is most valuable. Using data on the six US presidential elections from 1992 to 2012, we report the reductions in error obtained by averaging forecasts within and across four election forecasting methods: poll projections, expert judgment, quantitative models, and the Iowa Electronic Markets. Across the six elections, the resulting combined forecasts were more accurate than any individual component method, on average. The gains in accuracy from combining increased with the numbers of forecasts used, especially when these forecasts were based on different methods and different data, and in situations involving high levels of uncertainty. Such combining yielded error reductions of between 16% and 59%, compared to the average errors of the individual forecasts. This improvement is substantially greater than the 12% reduction in error that had been reported previously for combining forecasts.