13
expenses incurred to “learn” about the actual quality of the good increases variable costs of
production, and hence it is optimal to cut back on the output rate.
As mentioned before, stronger assumptions are needed to sign the last two derivatives
of interest. This is a direct result of the structure of the problem, where the strength of the
demand for the valued attribute enters by itself in the two necessary conditions. The problem is
that as a increases, there is an incentive to increase both the rate of output and the stringency
of the QAS, since it increases the marginal benefit part in equations (3) and (4). However, as
long as the technology is not nonjoint in inputs (see Chambers), increasing either variable
potentially has the effect of increasing the marginal-cost side of the other equation, thus
making the net change ambiguous. The intuition is that when the output rate increases, so does
the marginal costs associated with any given QAS. Also, increases in the profitability of the
market for value-added products provide incentives to monitor product quality more closely to
delay transition to the second state. However, this increases marginal costs of production. If it
is appropriate to assume that the technology is nonjoint in inputs, then ∂ 2π∕ ∂y ∂s = 0 obtains,
and both ∂y */∂a and ∂s */∂a are positive whenever revenues and marginal revenues increase
with the strength of the demand parameter.
Duopoly Processors with Public Reputation
We consider first the situation where an entire industry can lose consumer trust as a result of
the actions of one participant. Hennessy, Roosen, and Miranowski model a related issue and
conclude that even when firms in the food industry may profit by increased investments in
safety (assuming a leadership role), they may obtain higher levels of benefits by free riding on
the efforts of other chain participants. In the first state of this case, all processors have a good
reputation. In the second, all sellers are punished by consumers.
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