Enterprise Risk Management Through Strategic Allocation of Capital

This article presents a conceptual framework for operationalizing strategic enterprise risk management (ERM) in a general firm. We employ a risk‐constrained optimization approach to study the capital allocation decisions under ERM. Given the decision maker's risk appetite, the problem of holistically managing enterprise‐wide hazard, financial, operational, and real project risks is treated by maximizing the expected total return on capital, while trading off risks simultaneously in Value‐at‐Risk type of constraints. This approach explicitly quantifies the concepts of risk appetite and risk prioritization in light of the firm's default and financial distress avoidance reflected in its target credit rating. Our framework also allows the firm to consider a multiperiod planning horizon so that changing business environments can be accounted for. We illustrate the implementation of the framework through a numerical example. As an initial conceptual advancement, our formulation is capable of facilitating more general ERM modeling within a consistent strategic framework, where idiosyncratic variations of firms and different modeling assumptions can be accommodated. Managerial implications are also discussed.     

Testing whether waterfowl hunting benefits increase with greater water deliveries to wetlands

The change in waterfowl hunting benefits due to an increase in water deliveries to the levels required for biologically optimal wildlife refuge management at California's San Joaquin Valley National Wildlife Refuges are estimated with the Travel Cost Method, using both ordinary least squares and Poisson count data estimators. To test whether these increases were statistically significant, the Krinsky and Robb technique was used to find confidence intervals around the consumer surplus point estimates. The increases in consumer surplus were found to be statistically significant in 5 of the 6 refuges based on OLS regression estimates and in all 6 refuges using Poisson count data regression estimates. In addition, a comparison of the marginal value of an acre-foot of water in consumptive recreational use versus agriculture use is made, with the finding that the marginal value of water in waterfowl hunting was greater than the marginal value of water in agriculture for one of the six refuges.     

RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models,and Relations to Other Models and Measures in DEA

Generalized Efficiency Measures (GEMS) for use in DEA are developed and analyzed in a context of differing models where they might be employed. The additive model of DEA is accorded a central role and developed in association with a new measure of efficiency referred to as RAM (Range Adjusted Measure). The need for separately treating input oriented and output oriented approaches to efficient measurement is eliminated because additive models effect their evaluations by maximizing distance from the efficient frontier (in ₁, or weighted ₁, measure) and thereby simultaneously maximize outputs and minimize inputs. Contacts with other models and approaches are maintained with theorems and accompanying proofs to ensure the validity of the thus identified relations. New criteria are supplied, both managerial and mathematical, for evaluating proposed measures. The concept of approximating models is used to further extend these possibilities. The focus of the paper is on the physical aspects of performance involved in technical and mix inefficiencies. However, an Appendix shows how overall, allocative and technical inefficiencies may be incorporated in additive models.