the costs of purchasing permits to offset emissions) that the manager of the nth unit
expects to incur having retrofitted his unit with technology i. I define a compliance
frontier function Kn(vni). I assume: K'n(vni) < 0, Kn(vni) > 0 because the compliance
frontiers of all the units in the sample are negatively sloped and convex to the origin.
The location of each point on a generator’s compliance cost frontier is determined
by pre-retrofit characteristics of the unit (such as nameplate capacity, firing type,
furnace dimensions, etc.), the expected permit price and expected future production
levels. For the purpose of modeling the compliance decision, I assume that the plant
manager can choose any point on its continuous, convex compliance frontier Kn(vni).
In the empirical model, the decision is represented more realistically as a choice among
discrete points that define the frontier
I assume that plant managers minimize the present value of expected compliance
costs subject to the constraint that the chosen compliance strategy must lie on the
least-cost compliance frontier Kn(vni). Let Cni represent the compliance costs that
the manager of the nth unit expects to incur, having adopted compliance strategy i.
I assume that the variable and capital compliance cost components enter additively
into the compliance cost function of each firm:
(Tn
I {Vnitqnt + τt(mniQnt
J
t=Q
^nt)}e ritdt + βкsnKn(vni), (1)
where Vni = Vni + τmni. The manager expects to produce qnt kWh of electricity in
time t.13 Vnit represents the anticipated variable costs of producing electricity while
operating control technology i, net of permit purchases. I assume that all firms are
price takers in the permit market; the permit price τ is assumed to be exogenous
to the firm’s compliance decision. The unit’s permit allocation is Ant^, the post-
retrofit emissions rate is mni. The total capital cost is equal to the installation cost