SUMMARY

A Real Option Approach to Valuing Food Safety Risks

Victoria Salin
Assistant Professor
Department of Agricultural Economics
Texas A&M University
e-mail: v-salin@tamu.edu
Tel: (409) 845-8103

Investors will risk capital in an industry only if they believe that the future rewards outweigh the risk. Investors considering projects in the food industry are concerned about how a food safety problem might affect future cash flows from the investment. While food borne disease outbreaks may be rare events, a few incidents in recent years have dramatically reduced the revenues of the firms associated with the problem. This research provides a first attempt to link food safety risks to investment decisions, using the real option method of valuing the effects of uncertainty. The form of the model used here accounts for food safety risks by adding the possibility of a discrete drop in future cash flows to the stochastic process for future returns.

The results are constrained by the lack of data on the value of revenues lost as a result of food safety problems. The Food Safety and Inspection Service data on meat products recalled for bacterial contamination provides information on quantity; further investigation would be required to estimate values. Using a hypothetical investment project and various levels of the food safety risk parameters in the model, option values range from 39% to 59% of sunk costs of the project. Option values are interpreted as the opportunity cost of immediate investment, or the value of waiting until some uncertainty is resolved. These outcomes suggest that there are significant incentives to postpone investments due to uncertain future cash flows.

The probability of occurrence of a problem (the exponential hazard rate parameter) is the dominant food safety parameter in determining real option values in this model. This model structure is appropriate if business decision-makers believe that the probability of a food safety event occurring is more important than the size of the event, in terms of the decrease in cash flows for the firm. If further inquiry reveals that decision-makers are less concerned with frequency of problems than with scale of the problem, then an alternative model structure must be considered.

While it is clear that the chance of occurrence is the main determinant of option values, the direction of its effect is ambiguous. A decrease in the probability of occurrence of food safety problems can either raise or reduce real option values. One would expect that a decrease in risk would reduce option values. If a specific investment project falls in the range at which reduction in the probability parameter increases option values, then HACCP would not stimulate more rapid investment in food industry modernization. Researchers need to understand this ambiguity and its driving forces. The unexpected results occur when projects are smaller and when the probability of occurrence of a problem is very low.

The numerical experiments also revealed a range of parameters in which reductions in both the probability of occurrence and in the scale of the food safety problem reduced option values. If HACCP programs significantly affect the probability of outbreaks, then HACCP has long-term financial implications for firms and for the food industry overall, through the linkage to investment decisions. Risk reduction accomplished through HACCP would be an incentive for more rapid investment, which would enhance efficiency and could offset some costs of HACCP implementation.

This examination of financial decisions under uncertainty points out some specific data needs for evaluating business risks related to food safety. Understanding what factors determine the hazard rate parameter is the first target, according to this research. The probability of a drop in cash flows resulting from a food safety event may be defined at the firm level, and could perhaps be understood by surveys or interviews to elicit subjective probabilities or tolerances. It is also possible that food safety events in another firm affect cash flows industry-wide. Such spillover effects can be estimated from commodity market data or stock price data.

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