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Abstract
Food risks may be caused by moral hazard, i.e. by opportunistic
behaviour of upstream sellers who exploit the fact that many food
product qualities remain uncertain to downstream buyers in the
course of conventional market transactions (credence qualities).
Due to this lack of market transparency buyers run the risk to pay
premium prices for inferior products (quality risks); furthermore,
they run the risk to use or consume substances which are harmful
(health risks). Therefore, they will want to design optimal contracts
and controls preventing opportunistic behaviour. Usually, however,
buyers cannot contract contingent on the actions of upstream
sellers because they cannot observe them directly (information
asymmetry).
Motivated by the obviously game-theoretic nature of the problem,
we investigate the potential of principal-agent-models for the analysis
of food risks induced by opportunistic behaviour. We identify a
binary stochastic moral hazard model which is able to represent the
microeconomic situation of buyers (principals) and sellers (agents)
adequately. On the one hand, the model considers the remuneration
costs which are needed to induce compliance. On the other hand, it
accounts for direct costs and benefits of control as well as a limited
traceability caused by the multiple agents setting of most food risk
problems. If we know the costs of compliance, the stochastic relationship
between the agent’s action and the product quality, and the
traceability coefficient, we are able to determine the optimal control
intensity and price for any cost of control function and predefined
upper limit of the imposable sanction.
For practical applications the main problem will be how to procure
empirical data. The manageable data requirements of the binary
model qualify it as a ready to use model for future applications: first,
it can be used in positive analyses of food chains in order to detect
the hot spots where food risks induced by opportunistic behaviour
are to be expected for economic reasons. Secondly, it can be used
in normative analyses in order to identify contractual designs which
induce compliance at minimum costs. Thirdly, it can be used in
order to compare the efficiency of different system structures taking
into account the costs of change.